Cancer patients experience uncertainty about their illness, symptoms, treatment, themselves, their relationships, and their future (Mishel, 1990; Ferrell et al., 1998; O’Hair et al., 2003; O’Hair et al., 2008; Thompson and O’Hair, 2008). This can be both a positive and a negative state of not knowing (Brashers, 2001). These feelings of uncertainty may change during the course of the disease and treatment, but continue in survivorship (McKinley, 2000; Gill et al., 2004; Miller, 2014). According to the Uncertainty Management Theory (UMT), individuals aim to manage—i.e., to reduce, increase, or maintain—their uncertainties by seeking or avoiding information (Brashers et al., 2000; Link and Baumann, 2022a). Thus, ‘information needs’, which can be defined as the patient’s “recognition that their knowledge is inadequate to satisfy a goal, within the context/situation that they find themselves at a specific point in the time” (Ormandy, 2011), arise from the cancer patient’s uncertainty perception in a particular stage and context of illness, and are possible motivators of health information seeking and avoiding (Brashers et al., 2000; Kahlor, 2010), which have already been researched comprehensively in the context of cancer (Miller, 2014).

Studies on cancer information behavior mainly focus on active, needs-oriented information-seeking, i.e., a purposeful acquisition of information from selected information sources via specific channels to achieve goals like knowledge gain, attitude formation, decision making, or coping with uncertainties (Johnson and Meischke, 1993; Brashers, 2001). Most cancer patients, especially those with higher income and education, are active information seekers (Finney Rutten et al., 2016). But some individuals receive information only when they get in touch with it in everyday media use (information scanning; Niederdeppe et al., 2007; Grimm and Baumann, 2019). Finally, there is also information avoidance, meaning that the acquisition of available but potentially unwanted cancer-related information is deliberately not used or even actively avoided (Emanuel et al., 2015; Grimm and Baumann, 2019). Individuals with more pessimistic beliefs about the prevention and treatment of cancer, who are less health literate and less trusting of information sources, are more likely to avoid cancer information (Link and Baumann, 2022b). Studies report mixed results on sociodemographic factors that predict information avoidance (Link and Baumann, 2022b). A higher socioeconomic status seems to reduce the likelihood of health information avoidance (Ramanadhan and Viswanath, 2006; Chae, 2016; Nelissen et al., 2017; Chae et al., 2020; Link and Baumann, 2022b).

Several theoretical models help to explain the motivations and barriers of cancer information seeking, such as the Comprehensive Model of Information Seeking (CMIS, Johnson and Meischke, 1993), and the Planned Risk Information Seeking Model (PRISM; Johnson and Meischke, 1993; Kahlor, 2010; Hovick et al., 2014). The latter has already been applied and adjusted to the case of cancer information avoidance (e.g., Link and Baumann, 2022b). As the CMIS suggests, both sociodemographic and information carrier factors can contribute to or be barriers to (successful) information-seeking (Johnson and Meischke, 1993). On the information side, the sheer quantity of available health information can lead to information overload (Viswanath et al., 2012). The quality and depth of the available information are difficult to verify for the survivor, and much false information is circulating on the Internet (Arora et al., 2008; Maddock et al., 2011; Viswanath et al., 2012). On the individual side, the capability to assess the quality of and understand information can differ by the individual, e.g., depending on education level (Arora et al., 2008; Hesse et al., 2008; Maddock et al., 2011). Information carrier factors can also be applied to information preferences, such as the preferred delivery of information, e.g., the type of media or source (Johnson and Meischke, 1993).

Cancer patients undergo a so-called cancer journey from diagnosis to survivorship or palliative care (Mistry et al., 2010). Apart from different aspects of (medical) care needs at each stage of the continuum, the need for information in general, the relevance of different cancer-related information, and preferred sources and communication formats are changing throughout the cancer journey (Grimm and Baumann, 2019; Squiers et al., 2005).

Cancer patients thus undergo a cancer information seeking journey with changing informational and supportive needs and behaviors at each stage (Grimm and Baumann, 2019; Mistry et al., 2010; Squiers et al., 2005). Their information needs and behaviors vary throughout their illness (e.g., regarding the topics of interest) and differ by cancer type (Tan et al., 2015). Some still wish to be well informed about all aspects of their illness after completing treatment (Mistry et al., 2010; Hoekstra et al., 2014; Fletcher et al., 2017; Johnston et al., 2021), some, however, may want to distance themselves from this episode of illness in life and thus avoid information concerning cancer (Link and Baumann, 2022b).

When cancer survivors are given information about long-term consequences around the time of their diagnosis, they may feel too distressed and anxious to understand and process these potentially frightening facts or probabilities, and thus prefer not to be informed; they may also be concerned about whether they will recall this information later in their survivorship (van Osch et al., 2014; Fletcher et al., 2017). The amount of information and use of complex medical terms can also prevent survivors from information involvement (Kessels, 2003; van Weert et al., 2011; Fletcher et al., 2017). Although cancer survivors still visit their healthcare provider more often than patients without a cancer history, they still report unmet information needs (Soothill et al., 2001; Harrison et al., 2011; Hoekstra et al., 2014). They prefer their healthcare providers as a source of information but feel that the information obtained is insufficient (Finney Rutten et al., 2006; Chou et al., 2011; Finney Rutten et al., 2016). This leads them to use the Internet for acquiring additional health- and cancer-related information (Finney Rutten et al., 2006; Chou et al., 2011; Finney Rutten et al., 2016).

Apart from differences along the cancer journey, cancer survivors are a diverse group with individually varying needs and behaviors. Health disparities due to race, ethnicity, and socioeconomic status (SES), such as differences in mortality, the likelihood of developing cancer, general health status, and discrimination in healthcare, are reported (Aziz and Rowland, 2002; Braveman and Tarimo, 2002; Ward et al., 2004; Adler and Rehkopf, 2008; Polite et al., 2017; Butler et al., 2020). People from ethnic minorities are less likely to survive cancer for five or more years across several cancer domains (Ward et al., 2004; Polite et al., 2017). Racial disparities in cancer outcomes, follow-up, and long-term care are reported (Butler et al., 2020). Cancer survivors with lower SES tend to participate less in rehabilitation services and have unmet needs in that domain (Holm et al., 2013). There are general communication inequalities linked to these health-related social inequalities, such as access to and use of information channels and services, attention to and processing of health information, and capacity and ability to respond to information provided (Viswanath, 2006). Cancer survivors from ethnic minorities are also less likely to seek information and have more problems obtaining it (McInnes et al., 2008; Walsh et al., 2010). SES is further related to information seeking in cancer patients, with seeking information from medical and nonmedical sources being more likely for higher educated patients (Lee et al., 2012).

Apart from health and communication disparities due to social inequalities, survivors diagnosed in CAYA years are especially vulnerable and affected by long-term and late effects, since cancer in these life stages can affect physical and mental development, e.g., maturation, education, and hormones. They could also have greater information needs, since information given during diagnosis and treatment was given to the parents instead of the survivors (Grossi, 1998; Gianinazzi et al., 2014; Byrne et al., 2022).

As described above, the information needs, information-seeking behaviors, information preferences, as well as the information barriers and avoidance behaviors of LTCS have been found to differ from those in earlier stages of the cancer patient journey. Further, they are supposed to differ in terms of vulnerabilities, such as race, SES, and age at diagnosis. To develop and provide suitable informational support tailored to the needs of LTCS, a synthesis of research evidence is necessary. Therefore, the following research questions arise:

Five databases were selected based on their relevance to oncology and health communication, and were searched using relevant keywords: Medline (via PubMed), Scopus, PsycNET, Communication & Mass Media Complete (via EBSCOhost), and Web of Science. A broad search strategy was developed by the first author, consisting of a combination of the terms ‘information’, ‘cancer’, and ‘survivor’ with respective synonyms. The search in the title and abstract field returned a large number of articles about the medical needs of cancer survivors rather than their informational needs. Due to limited project duration and staffing, the review was limited to a title-based search. While this method was necessarily selective, it increased the chances of finding studies that are most relevant to the theme, as a topic in the title indicates a stronger focus on it. Studies that only addressed information needs peripherally – for example, through a single open-ended question within a broader survey — were intentionally excluded. The full search strings and raw export data are available in Appendix A.

The population of LTCS was defined as people living with a cancer diagnosis for more than 5 years. The key concepts of ‘Advice’ and ‘Information’ in this study were defined as any written or spoken interpersonal or media-mediated information, data, knowledge, or recommendation that was not part of medical or psychological therapy, i.e., no psychological, genetic, diet or activity counseling or programming from a healthcare provider or professional, survivorship care planning or medical services. Information and advice about these services and topics are included, such as details on where to find them and the types of services available.

‘Information needs’ were defined as the motivational dispositions, information requests, or expressions of information wanted to have, while ‘preferences’ referred to the formal aspects of information needed, i.e., the type, delivery mode, the portrayal, the way of access, or the time survivors wanted to receive the information. ‘Behavior’ was defined as any action to seek, scan, non-seek, or avoid information or advice self-reported by cancer survivors, and ‘Barriers’ as conditions or characteristics, e.g., sociodemographic ones, to finding and understanding information or advice self-reported by cancer survivors. Inclusion and exclusion criteria for study selection using the Population-Concept-Context (PCC) framework (Peters et al., 2020) are presented in Table 1.

Studies with survivors at different stages of survivorship were included if either long-term survivors (≥5 years since diagnosis) were investigated as a separate group or time since diagnosis was included as an independent or control variable in the analysis.

Studies with cancer survivors participating in trials, programs, or interventions were excluded because the experiences in these programs may not represent both the broader survivorship population due to selection bias and everyday life due to the controlled environment. Quantitative, qualitative, and mixed-methods studies, including those with primary or secondary data analyses, were included in the review to capture a broad insight into the topic. Searches were limited to empirical journal articles in peer-reviewed journals, in German and in English. No exclusion criteria were applied to geographical location, cancer type, age at diagnosis, and current age of the survivors to scope the breadth of the available literature.

Search results from all five databases were exported into Excel, and duplicates were removed. For the remaining results, a title screening was conducted to match the PCC framework. Screening titles first is more efficient and tends to lead to the same recall as screening titles and abstracts together (Mateen et al., 2013). The remaining articles were researched, and abstracts were screened for population, context, and concept. After excluding the irrelevant studies, the full texts of the remaining articles were searched, downloaded, and screened for eligibility criteria. The process of inclusion and exclusion was conducted by the first author and is presented in the PRISMA Flow Chart (see Figure 1).

The following information was extracted and summarized for each study:

Study reference: Author, journal, year of publication, country where the study was conducted, publishing language.

Participants: Type(s) of cancer, age at study (range/mean), life stage at diagnosis (CAYA / non-CAYA), gender, ethnicity, sample size.

Content: Theoretical framework, information needs / barriers / behaviors (seek, non-seek, scan, avoid) / preferences and factors associated with it.

Study design: Qualitative or quantitative, experimental design (yes/no), limitations.

Ethnic groups to describe the studies’ populations were derived from the Health Information National Trends Survey (HINTS; Finney Rutten et al., 2006) and included White, Asian, Hispanic, Black, and Other. Other included Non-White, Non-Hispanic minorities, e.g., Arab migration background or Indigenous background, such as Aboriginal or Alaskan Native. Studies were coded CAYA if they explicitly mentioned childhood or AYA cancers.

Studies were first categorized according to their main topic to answer the research questions: information needs, information seeking and preferences, and information avoidance and barriers. The theoretical models used in the studies were coded openly and then aggregated. Information barriers were analyzed in terms of the CMIS’s characteristics of the media and individual characteristics (Johnson and Meischke, 1993), coded openly and inductively condensed afterward. The categories for information topics were derived from Fletcher et al. (2017) and Johnston et al. (2021). Categories describing the reported information behaviors were based on the UMT (Brashers et al., 2000; Brashers et al., 2002) and extended by Grimm and Baumann’s (2019) summary of cancer-related information behaviors to include cancer information seeking, non-seeking, scanning, and avoiding. Information preferences were coded in terms of the preferred information source, form (e.g., website), and timing of the information.

For all dimensions, associated factors were coded. Derived from the CMIS (Johnson and Meischke, 1993), these included the sociodemographic variables “current age,” “gender,” “race or ethnical background,” “self-reported health status,” “education,” and “income” as well as the cancer-specific factors “type of cancer,” “age at diagnosis,” and “time since diagnosis” as health-related factors. An open category for other factors was included, e.g., for the perceived seeking control and seeking-related subjective norms as proposed by PRISM (Kahlor, 2010). The factors were coded if they were found to be associated with information needs or behaviors of LTCS, and the specific empirical relation was summarized openly. The full code sheet is available in Appendix B.

As specified in the PRISMA-ScR, a formal quality assessment of the included studies was not conducted (Tricco et al., 2018). The general characteristics of the included studies were mapped using the PCC framework. An overview of the included articles is presented in Table 2.

The studies included in the review revealed that LTCS still have unmet information needs, most on general health topics, cancer, and recurrence; comorbidities, and also on genetic risks and testing, fertility and sexuality issues, psychological issues or help, financial issues, diet and nutrition, and sports and activity (McInnes et al., 2008; Kent et al., 2012; Bernat et al., 2016b; O’Malley et al., 2016; Playdon et al., 2016; Benedict et al., 2018; Diver et al., 2018; Scarton et al., 2018; Albers et al., 2020; Lehmann-Laue et al., 2020; León-Salas et al., 2022; see Table 3). Younger survivors tend to have more information needs (Kent et al., 2012; Playdon et al., 2016; Diver et al., 2018; Scarton et al., 2018; Albers et al., 2020; see Table 3). Poorer general health, lower quality of life, higher symptom burden, or mental health problems are associated with greater information needs (McInnes et al., 2008; Bernat et al., 2016b; Playdon et al., 2016; Benedict et al., 2018; Hovén et al., 2018; see Table 3). Survivors diagnosed in earlier years of their lives tend to have more information needs than those diagnosed later in life (Kent et al., 2012; Playdon et al., 2016; see Table 3). Information needs tend to decrease with increasing time since diagnosis or approximately ten years after diagnosis (McInnes et al., 2008; Albers et al., 2020; see Table 3).

Race. Concerning race, four studies (11.1%) found non-White participants to have greater information needs than White LTCS (Kent et al., 2012; Bernat et al., 2016b; O’Malley et al., 2016; Playdon et al., 2016; see Table 3).

Lower SES. Income was a significant factor in one study (2.78%; Bernat et al., 2016b; see Table 3), with higher income associated with greater information needs. Higher education was found to be associated with greater information needs in one study (2.78%; Playdon et al., 2016; see Table 3), whereas five studies (13.89%) found education not to be significant (McInnes et al., 2008; Kent et al., 2012; Bernat et al., 2016b; O’Malley et al., 2016; Diver et al., 2018). One study found that cancer survivors reporting inadequate financial resources and lower social support were more likely to report health promotion and insurance-related information needs (2.78%; Kent et al., 2012; see Table 3).

CAYA. CAYA LTCS appear to have information needs in similar domains to non-CAYA LTCS in 84.62% of the studies on CAYA (n = 11; Blacklay et al., 1998; Gianinazzi et al., 2014; Lie et al., 2015; Vetsch et al., 2017; Claridy et al., 2018; Hovén et al., 2018; Christen et al., 2019; Kelada et al., 2019; Billman et al., 2022; Hou et al., 2022; Thorsen et al., 2022; see Table 3). Also, worse physical and mental health seems to contribute to greater information needs in 46.15% of the studies on CAYA (Gianinazzi et al., 2014; Vetsch et al., 2017; Hovén et al., 2018; Christen et al., 2019; Vetsch et al., 2020; Thorsen et al., 2022; see Table 3). In contrast to non-CAYA LTCS, current age, age at diagnosis, and time since diagnosis do not appear to be associated with information needs in CAYA cancer survivors, as seven studies (58.33%) reported no associations (Blacklay et al., 1998; Gianinazzi et al., 2014; Vetsch et al., 2017; Hovén et al., 2018; Christen et al., 2019; Kelada et al., 2019; Vetsch et al., 2020; Thorsen et al., 2022).

Concerning information behaviors, the studies included in this review mainly reported on the information-seeking or non-seeking behavior of non-CAYA LTCS (see Table 3). Across the studies, the most frequently mentioned source for information seeking was the Internet (Mayer et al., 2007; Hesse et al., 2008; Bernat et al., 2016a; Finney Rutten et al., 2016; Linden et al., 2019; Chua et al., 2021; Davis et al., 2021), although some LTCS seemed to prefer receiving information from their healthcare provider instead (Mayer et al., 2007; Hesse et al., 2008; Chua et al., 2021; see Table 3). According to the studies, LTCS seek information on general health topics, cancer and recurrence, genetics, sexuality and fertility, and psychological wellbeing (Chou et al., 2011; Bernat et al., 2016a; Finney Rutten et al., 2016; Linden et al., 2019; Jiang and Liu, 2020; Chua et al., 2021; Davis et al., 2021; Fareed et al., 2021; see Table 3). Younger age seems to predict more health information seeking, especially on the Internet (Mayer et al., 2007; Hesse et al., 2008; Chou et al., 2011; Finney Rutten et al., 2016; Linden et al., 2019; Jackson et al., 2020; Jiang and Liu, 2020; Chua et al., 2021; see Table 3). Findings on the association with gender are inconclusive.

Longer time since diagnosis may decrease the likelihood of seeking cancer-related health information in general and on the Internet, and increase the likelihood of being a non-seeker (Chou et al., 2011; Finney Rutten et al., 2016; Linden et al., 2019; Chua et al., 2021; see Table 3), but other studies found no relation (Mayer et al., 2007; Hesse et al., 2008; McInnes et al., 2008; McCloud et al., 2013; Claridy et al., 2018; Jackson et al., 2020; Jiang and Liu, 2020; Davis et al., 2021; Fareed et al., 2021). Concerning general health status, two studies reported that survivors with better health were more likely to use the Internet (Chou et al., 2011; Fareed et al., 2021; see Table 3). Two studies found no relation between information-seeking and health status (Mayer et al., 2007; Jiang and Liu, 2020). Other studies did not report on the relationship between health status and information seeking.

Other factors increasing the likelihood of information-seeking behavior are the progress of the cancer and frequent Internet use (Linden et al., 2019; see Table 3). Internet access, health-related Internet use, and trust in online health information were also found to be associated with more information seeking on the Internet (Jiang and Liu, 2020; see Table 3).

LTCS described being too preoccupied during the diagnosis and treatment phase to process information on long-term effects (Boulton et al., 2015; see Table 3). In long-term survivorship, they prefer receiving personalized information in written or multimedia formats, including medical information and stories from other survivors, but also want to get information from their healthcare provider, preferably in a supportive setting (Mayer et al., 2007; Boulton et al., 2015; Playdon et al., 2016; Christen et al., 2019; see Table 3).

As motivation for seeking health information, survivors mentioned medical reasons like being diagnosed with a new health problem, unanswered questions after a visit to the doctor or clinic, being prescribed a new treatment, test, or medication, and having a medical condition, like high blood pressure or diabetes (Claridy et al., 2018; see Table 3). On top of that, learning more about the effects of the treatment they received, seeing or hearing something on the news they wanted to learn more about, and wanting to change their diet or activity habits were motivators to seek health-related information (Claridy et al., 2018; see Table 3).

Race, lower SES. While information seeking in general or on the Internet was not a predicted by race in any study where it was controlled (n = 5; 13.89%; Mayer et al., 2007; Hesse et al., 2008; Finney Rutten et al., 2016; Jackson et al., 2020; Davis et al., 2021), a higher socioeconomic status, meaning higher income and education, appeared in 19.44% of the studies to be positively associated with health information seeking in general (Hesse et al., 2008; Chua et al., 2021; Davis et al., 2021; see Table 3) and on the Internet (Chou et al., 2011; Finney Rutten et al., 2016; Fareed et al., 2021; see Table 3).

However, 13.89% of the studies found no difference in education (Mayer et al., 2007; Linden et al., 2019; Jiang and Liu, 2020) and income (Hesse et al., 2008; Jiang and Liu, 2020). Further factors increasing the likelihood of information-seeking behaviors are having a regular healthcare provider (Mayer et al., 2007; see Table 3), having a job, and private housing (Chua et al., 2021; see Table 3). None of the identified studies analyzed specific information preferences of Non-White and ethnic minority LTCS and LTCS with lower SES.

CAYA. Studies on the information behaviors of CAYA LTCS were sparse. Besides turning to their parents and healthcare providers, CAYA survivors seem to use the Internet to seek information and are more likely to do so if they are younger, higher educated and have poorer general health status (Claridy et al., 2018; Billman et al., 2022; see Table 3). They seek information on general health, cancer and recurrence, and comorbidities (Claridy et al., 2018; Billman et al., 2022; see Table 3). Especially CAYA cancer survivors reported limited knowledge of their cancer treatments, which leaves them unprepared to manage their health in survivorship (Billman et al., 2022). They prefer written information in a personalized form, consider receiving a refreshment of information once they reach adulthood as useful, and like to have information available continuously (Gianinazzi et al., 2014; Lie et al., 2015; Christen et al., 2019; Vetsch et al., 2020; see Table 3).

According to the literature under study, information barriers of LTCS can be categorized into personal barriers and informational barriers. On the individual side, missing time and difficulties in finding information (including technical access), frustration while searching for it, difficulties in assessing the information’s quality, understanding it, trusting it, and missing health-related self-efficacy were found to be barriers to information seeking (Mayer et al., 2007; McInnes et al., 2008; McCloud et al., 2013; Bernat et al., 2016b; Linden et al., 2019; Chua et al., 2021; Davis et al., 2021; see Table 3). On the information side, the (perceived) quality and relevance of the information, the sheer volume of it on the Internet and the effort to find it were barriers to successful information seeking and satisfying information needs (Mayer et al., 2007; Hesse et al., 2008; Bernat et al., 2016b; Linden et al., 2019; Chua et al., 2021; Davis et al., 2021; see Table 3).

Race. There were no reports on information barriers and avoidance behaviors of non-White or ethnic minority LTCS.

Lower SES. One study found information avoiders are more likely to be female, with higher debt, lower income, and aged under 50 years (McCloud et al., 2013). Younger men also showed a tendency to avoid information in one study, where a lower education level increased the likelihood of information avoidance (McCloud et al., 2013). One study found that lower income and lower health information-seeking self-efficacy were associated with more negative information-seeking experiences (Bernat et al., 2016a). The feeling that information was too hard to understand increased with lower levels of education (Bernat et al., 2016a).

CAYA. CAYA cancer survivors reported that the resources available to them fall short of their information needs (Billman et al., 2022). A barrier to adequate health information on their side is the uncertainty about who to ask and where to look, and the ability to judge whether information is relevant to them (Lie et al., 2015; see Table 3). On the information side, the sheer volume of information available on the Internet was reported as a barrier (Lie et al., 2015; see Table 3). On top of that, CAYA cancer survivors tend not to trust their general health provider and oncologist to possess sufficient knowledge of cancer long-term and late effects (Lie et al., 2015; see Table 3). When contacting their oncologist, CAYA survivors felt the oncologist would be too busy to be bothered with their ‘minor’ worries or that their illness would be too long ago for the oncologist to be the right person to approach (Lie et al., 2015).

Only five studies (13.89%) were based on a theoretical model. Two studies used Bandura’s Self-Efficacy Theory (McInnes et al., 2008; Kent et al., 2012). One (McCloud et al., 2013) used Uncertainty Management Theory and the Structural Influence Model (Viswanath et al., 2007), another derived their interview questions from the Health Belief Model and Uses and Gratifications Theory (Scarton et al., 2018). Another one used the CMIS to model their study (Mayer et al., 2007).

Limitations acknowledged by the authors included recruiting participants from single institutions, e.g., cancer groups or centers, and low response rates (Hesse et al., 2008; Kent et al., 2012; McCloud et al., 2013; Gianinazzi et al., 2014; Boulton et al., 2015; Bernat et al., 2016a; Bernat et al., 2016b; Finney Rutten et al., 2016; Benedict et al., 2018; Diver et al., 2018; Scarton et al., 2018; Christen et al., 2019; Albers et al., 2020; Jackson et al., 2020; Chua et al., 2021; Fareed et al., 2021; Hou et al., 2022; Thorsen et al., 2022; see Table 3). In addition, several authors reported a lack of representation of minorities in the participants (McInnes et al., 2008; McCloud et al., 2013; Boulton et al., 2015; O’Malley et al., 2016; Playdon et al., 2016; Davis et al., 2021; Billman et al., 2022; Hou et al., 2022; see Table 3).

Participants of the studies were more educated than cancer survivors in general (Kent et al., 2012; Scarton et al., 2018; Albers et al., 2020; León-Salas et al., 2022; see Table 3), and expected to be either healthier than the population (Boulton et al., 2015; Lie et al., 2015; Diver et al., 2018; Kelada et al., 2019; Jiang and Liu, 2020; Fareed et al., 2021; see Table 3), or with higher physical burdens (Albers et al., 2020). Several studies could not explain all relevant relationships because they included only a limited number of variables, especially considering factors contributing to health information needs and behaviors (Mayer et al., 2007; McInnes et al., 2008; Finney Rutten et al., 2016; Playdon et al., 2016; Benedict et al., 2018; Kelada et al., 2019; Albers et al., 2020; Jackson et al., 2020; Chua et al., 2021; Fareed et al., 2021; Hou et al., 2022; Thorsen et al., 2022; see Table 3). Limited explanatory power was also reported as a limitation by the authors due to measuring complex phenomena with simplified items (McCloud et al., 2013; Bernat et al., 2016b; Finney Rutten et al., 2016; Vetsch et al., 2017; Kelada et al., 2019; Jiang and Liu, 2020; Davis et al., 2021; see Table 3).

Several studies gave recommendations, addressing the need for qualitative studies to gain in-depth insights into information needs and behaviors, and longitudinal studies to analyze the changes over time and in relation to different cancer survivorship states (Mayer et al., 2007; Chou et al., 2011; Playdon et al., 2016; Christen et al., 2019; Kelada et al., 2019; Jackson et al., 2020; Jiang and Liu, 2020; Chua et al., 2021; Davis et al., 2021; Hou et al., 2022; see Table 3). Interventions to assess the effectiveness of tailored information and individual care plans were also recommended (Kent et al., 2012; Bernat et al., 2016a; Bernat et al., 2016b; O’Malley et al., 2016; see Table 3).

The studies recommended practical improvements in doctor-patient interaction. The importance of both the practitioners as a source of information, supporting written information material, and providing information in a personal conversation was underlined (Boulton et al., 2015; Davis et al., 2021; see Table 3). Some studies recommended incorporating information on the Internet in the doctor-patient conversation, e.g., doctors should encourage patients to seek information online and educate them on how to find reliable information, and doctors should better prepare for conversations with Internet-informed patients (Mayer et al., 2007; Linden et al., 2019; Jiang and Liu, 2020; see Table 3). Other studies also recommended that other healthcare personnel provide information to LTCS to relieve the workload from doctors (Gianinazzi et al., 2014; Boulton et al., 2015; Kelada et al., 2019; Vetsch et al., 2020; Thorsen et al., 2022; see Table 3).

This scoping review offers valuable insights into the information needs and behaviors of long-term cancer survivors, thereby extending social science research on health by examining this vulnerable group. However, the findings should be interpreted in light of several limitations. A broad search strategy was employed to search the title section of databases; therefore, the included studies may not fully represent the current knowledge on long-term cancer survivors. Future research could consider a librarian or information specialist to develop the search string further. The first author conducted both the development of the search string and the screening process. Although inclusion and exclusion decisions were carefully evaluated based on the specified criteria and documented in detail, they still may have been biased. Studies from different regions were included in this review, with no regard to the cultural and systemic differences of the countries, e.g., in terms of health insurance and healthcare systems. Although information needs and behaviors can be observed in LTCS in general, the medical supply situation in the respective region can also impact needs, behaviors, and barriers. A comparison of national healthcare systems and supply situations, along with a subsequent interpretation of the findings within this context, is needed.

Furthermore, both quantitative and qualitative studies were included and treated as equally important, with no regard to sample size, recruitment method, or bias. This could over- or underestimate reported findings. This scoping review can only provide an overview of the existing literature in a systematic manner, without regard to the quality of the studies or analyzing the findings in relation to a meta-analysis. Since only studies published in peer-reviewed journals were included, they should generally meet research standards. Biased samples, such as those recruited only from members of cancer support groups, have been reported in the included studies and were not addressed in this review. A review with a subsequent meta-analysis could provide insight into the differing findings, especially regarding factors predicting LTCS’ information behavior, and consider effect sizes to minimize the over- or underestimation of findings.