A Comprehensive Review of Factors Influencing the Uncertainty of Diagnosis in Patients with Undetermined Fever ()
1. Background
Fever of Unknown Origin (FUO) is a common and challenging clinical condition. Its classic definition is a fever lasting ≥3 weeks, with multiple episodes of body temperature ≥38.3˚C, and no identifiable cause after ≥1 week of systematic investigation [1]. The etiology of FUO spans multiple systems, including infections, tumors, connective tissue diseases, and endocrine/metabolic disorders, and is characterized by prolonged diagnostic cycles, elusive causes, and recurrent symptoms [2]. The protracted diagnostic journey and unpredictable disease trajectory expose patients to prolonged health threats, making them highly susceptible to psychological crises centered on uncertainty in illness [3].
Uncertainty in illness refers to the state of cognitive imbalance experienced by individuals in disease contexts due to information gaps or unpredictable events, manifesting as impaired judgment regarding disease nature, progression, and prognosis. This condition can significantly exacerbate patient anxiety and depression while simultaneously reducing treatment adherence and quality of life [4]. The concept of uncertainty in illness was originally proposed by American nurse researcher Mishel, whose theoretical framework divides the dynamic process of uncertainty in illness into the predisposing factors, appraisal stage, coping stage, and adaptation stage, emphasizing Uncertainty in Illness’s negative impact on patient treatment adherence and quality of life [4].
Currently, domestic research on uncertainty in illness in FUO patients is limited to cross-sectional surveys, lacking integrated evidence to guide nursing practice. To systematically elucidate the impact mechanisms of uncertainty in illness in FUO patients, this study employs the Arksey and O’Malley systematic review framework [5]. Specifically, it systematically retrieves and analyzes relevant domestic and international literature to reveal the multifaceted mechanisms of uncertainty in illness in FUO patients. This review aims to provide a theoretical basis for developing evidence-based intervention strategies, thereby improving patients’ psychological experiences and clinical outcomes.
2. Literature Screening Method
2.1. Defining the Research Question
This study aims to investigate the factors influencing urinary incontinence (uncertainty in illness) in patients with fever of unknown origin (FUO). It seeks to comprehensively review and analyze various elements that may affect uncertainty in illness in this specific patient population, thereby providing a basis for developing targeted intervention measures.
2.2. Inclusion and Exclusion Criteria
Inclusion Criteria:
(1) Target Population: Studies focusing on patients with FUO and/or their caregivers. (2) Research Content: Literature examining uncertainty in illness influencing factors (including cross-sectional studies, cohort studies, and qualitative research). (3) Language: Literature published in Chinese and English. Exclusion Criteria: (1) Literature where the full text was unavailable. (2) Literature with ambiguous or incomplete original data.
2.3. Search Strategy
A multi-database search strategy was employed, systematically retrieving articles from PubMed, Web of Science, CNKI, Wanfang Database, and VIP Database. Additionally, manual searches of relevant references were conducted to supplement the literature pool. The search period spanned from the inception of each database to February 2025. The searches combined subject headings (MeSH/Thesaurus terms) with free-text terms. English search terms included: Fever of Unknown Origin, Fever, Uncertainty, uncertainty in illness, illness uncertainty. Chinese search terms included: 发热 (fever), 发热待查 (fever of unknown origin), 疾病不确定感 (illness uncertainty). Using PubMed as an example, the search query was structured as follows:for English searches, the query was: ((Fever of Unknown Origin[Title/Abstract]) OR (Fever[Title/Abstract])) AND (“Uncertainty”[Major]) OR [“uncertainty in illness”([Title/Abstract] OR “illness uncertainty” ) (‘Uncertainty’[Mesh] AND “Fever of Unknown Origin” [Mesh]).
2.4. Screening Strategy
The literature screening process strictly followed the workflow diagram (Figure 1). First, EndNote X9 reference management software was utilized to perform standardized deduplication. After deduplication, two researchers independently conducted the initial screening and double-checking. This stage primarily involved reviewing titles and abstracts to preliminarily assess whether the references met the established inclusion criteria. Potentially eligible articles identified during the initial screening proceeded to the full-text review stage. Should disagreements arise between the two researchers during any screening stage, a third researcher was consulted for professional arbitration. This process ensured the rigor and fairness of the literature screening, guaranteeing the high quality and reliability of the final included studies.
2.5. Data Extraction and Analysis
Researchers entered key information from included articles into Excel based on the research questions. Extracted data included authors, publication date, study type, sample size, research objectives, assessment tools, and data analysis methods.
3. Literature Screening Results
Figure 1. Literature screening flowchart.
The detailed literature screening process and outcomes are illustrated in Flowchart 1 (Figure 1). A total of 1608 articles were retrieved from relevant databases. After deduplication, 1323 articles remained. Following the abstract review, 1299 articles were excluded. Full-text reviews were conducted on the remaining 24 articles, resulting in 9 ultimately included.
3.1. Basic Characteristics of Included Studies
Specific details of the included studies are presented in Table 1.
Table 1. Basic characteristics of included literature.
Author |
Publication Date |
Research Type |
Sample Size (Examples) |
Research Objectives |
Assessment Tool |
Data Analysis Methods |
Yao Yebin et al. [3] |
2022 |
Cross-sectional study |
296 |
Analyzed the current status and influencing factors of disease uncertainty among FUO patients. |
General demographic questionnaire, Disease Uncertainty Scale, irritability, depression, and anxiety scores |
t-tests, one-way ANOVA, Pearson correlation analysis, multiple linear regression analysis |
Li Huan et al. [6] |
2018 |
Cross-sectional study |
60 |
Investigate the current status and influencing factors of disease uncertainty among FUO patients to provide a reference for subsequent nursing interventions. |
General Information Questionnaire, Disease Uncertainty Scale |
Descriptive analysis, t-tests, one-way analysis of variance, multiple linear stepwise regression analysis |
Fan lingli [7] |
2022 |
Case-control study |
80 |
Investigating the Effects of Tiered Psychological Intervention Combined with Systematic Health Education on Patients with FUO |
Illness Uncertainty Scale, Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, Treatment Adherence, Nursing Satisfaction |
t-test, chi-square test for categorical data |
Qian liping [8] |
2022 |
Case-control study |
100 |
Investigate the significance and impact of standardized health education provided by clinical care providers to patients with FUO. |
Nursing satisfaction rate and nurse-patient dispute rate, Disease Uncertainty Scale, Self-Care Competence Scale, Quality of Life Scale, Excellent medical compliance rate |
t-test, chi-square test for categorical data |
Wang Yun et al. [9] |
2021 |
Cross-sectional study |
162 |
Investigating the Current Status and Influencing Factors of Disease Uncertainty Among Outpatients with FUO |
General Information Questionnaire, Disease Uncertainty Scale |
t-test, chi-square test, logistic regression analysis |
Li Jia et al. [10] |
2023 |
Case-control study |
100 |
Analyzing the Effects of Evidence-Based Nursing on the Psychological Status and Adherence of Elderly Patients with Fever of Unknown Origin. |
The control group received routine care, while the observation group received evidence-based care. After one month, the psychological status, disease uncertainty, and compliance of patients in both groups were compared. |
t-test, chi-square test |
Kong xianghong et al. [11] |
2022 |
Case-control study |
100 |
Study the psychological care outcomes in fever clinic nursing centers. |
Standard care (control group), psychological care (study group) |
t-test, chi-square test |
Franklinet al. [12] |
2024 |
Structured Interview |
15 |
Understanding Parents’ and Doctors’ Perspectives on the Causes of FUO in Children |
Conduct semi-structured remote interviews |
|
Zhao aiyun [13] |
2024 |
Case-control study |
100 |
To explore the effects of a discharge readiness intervention program for caregivers of children with febrile seizures on the quality of discharge instructions and their perceived uncertainty about the illness, thereby providing guidance for post-discharge condition management and care of these children. |
General information on both groups of children and caregivers was collected before and after the intervention, including caregiver discharge readiness, quality of discharge instructions, uncertainty about the illness, and caregiving capacity. |
Independent samples t-test, chi-square test, repeated measures analysis of variance |
3.2. Factors Influencing Disease Uncertainty in Patients with
Fever of Unknown Origin
This study synthesizes evidence from nine included studies and found that uncertainty in illness among patients with fever of unknown origin (FUO) generally remains at moderate levels. According to reference [3], scores ranging from 32 to 74.7 indicate low levels, scores from 74.7 to 117.4 indicate moderate levels, and scores from 117.4 to 160 indicate high levels. Higher scores suggest stronger disease uncertainty. The Cronbach’s α coefficient was 0.928, and the content validity index was 0.92.
The uncertainty in illness in these patients is influenced by factors spanning four core dimensions: disease characteristics and course, personal cognition and psychology, sociodemographic and economic factors, and medical care and information support. Details are presented in Table 2.
Table 2. Factors influencing perceived disease uncertainty in FUO patients.
Classification |
Influencing Factors |
Disease Characteristics and Course Factors |
Course of Fever and Recurrence |
Prolonged fever duration (e.g., recurrent fever caused by viral infections, which may last up to one month) significantly increases patients’ doubts about treatment efficacy, leading to heightened disease uncertainty (higher MUSI scores) [9]. |
Due to the disease’s unknown etiology and protracted course, FUO patients experience uncertainty in the complexity and unpredictability dimensions (the highest-scoring dimensions on the MUIS scale) [6]. This difficulty in predicting when fever will occur and what accompanying symptoms may arise is central to their elevated uncertainty in illness. |
Perceived Severity of Illness |
Regression analysis confirmed that patients’ subjective perception of disease severity is a core influencing factor (P < 0.05). The more severe the perceived illness, the greater the tendency for patients to diminish their self-care abilities and restrict their social functioning, which consequently heightens feelings of uncertainty [6] [9]. |
Patients who believe that their illness will negatively impact their family’s financial situation often experience heightened psychological distress due to feelings of guilt, which indirectly increases their uncertainty in illness [3]. |
Individual Cognitive and Psychological Factors |
Level of understanding of the disease |
Low disease knowledge emerged as the primary predictor of uncertainty in illness in patients with Fever of Unknown Origin (FUO) (as a selected variable in the regression equation) [6]. This finding is consistent with the mechanism proposed in Mishel’s Uncertainty in Illness Theory: “insufficient cognitive capacity leads to an inability to explain pathological stimuli” [6]. |
Health education aimed at enhancing disease awareness (such as providing information on causes and treatment processes) has been shown to effectively reduce scores on the uncertainty and complexity dimensions of the uncertainty in illness scale [6] [10]. |
Negative Emotions nd Psychological State |
Anxiety, Depression, and Irritability Patients with unexplained fever exhibited a positive correlation between disease uncertainty and anxiety (SAS), depression (SDS), and introverted irritability (P < 0.05). Negative emotions exacerbated uncertainty by intensifying “distrust in treatment” and “pessimistic expectations regarding prognosis” [3] [6]. |
The Vicious Cycle of Uncertainty and Emotion The physical and emotional suffering caused by prolonged and repeated treatments intensifies depressive feelings [3]. In a bidirectional influence, this depression, in turn, acts to heighten disease uncertainty, thereby establishing a vicious cycle between emotional distress and cognitive uncertainty [3]. |
Socio-demographic and economic factors |
Age and Education |
Patients aged ≥60 years with primary school education or below scored higher on disease uncertainty (P < 0.01) [3], potentially due to impaired hearing/comprehension in elderly patients [8] and limited information access among those with lower education levels. |
Economic and Medical Payment Methods |
Patients with monthly incomes ≤3000 yuan and out-of-pocket medical expenses exhibited significantly heightened uncertainty (β = −6.429, P < 0.001), as financial strain directly exacerbated concerns about treatment continuity and costs [3]. Patients experiencing a “give-up” mentality due to treatment cost anxieties further reduced treatment adherence, thereby inversely amplifying uncertainty [3]. |
Marital Status |
Patients with poor marital status lack relevant family support and exhibit higher scores on disease uncertainty [3]. Mobilizing social support systems can alleviate feelings of loneliness [11]. |
Medical Care and Information Support Factors |
Information Support |
Healthcare providers’ failure to provide clear, personalized disease information (such as examination procedures and treatment rationale) is a significant source of uncertainty [10]. By “systematically retrieving evidence and translating it into patient-understandable information,” uncertainty scores can be significantly reduced [8]. |
Communication Quality |
Inadequate communication and fragmented health education can heighten patient concerns. One-on-one health education, weekly summary mechanisms, or a nursing model combining “tiered psychological intervention with systematic health education” [7] [8] [10] can reduce uncertainty by enhancing information transparency and providing emotional support. |
4. Discussion
4.1. The Duration of Fever and Perceived Disease Severity as Key
Drivers of Uncertainty in FUO Patients
The core characteristic of Fever of Unknown Origin (FUO) lies in its “prolonged fever with unknown etiology.” Its diagnostic spectrum is extensive, encompassing at least eight major categories and over 200 disease entities, including infections, tumors, and immune-inflammatory diseases. This objectively results in significant complexity and a protracted duration in the diagnostic and treatment process [14] [15].
The prolonged fever course and unknown etiology collectively disrupt patients’ cognitive expectations of the conventional “disease-treatment-recovery” pattern [11]. The persistent lack of clarity regarding the cause renders the disease progression—including the timing of fever episodes, accompanying symptoms, and clinical outcomes—highly unpredictable. This sense of loss of control over the disease course directly elevates the dimensions of “complexity” and “unpredictability” within the overall uncertainty in illness [11] [13].
Concurrently, a patient’s subjective perception of disease severity not only reflects their physiological status but also triggers a negative cycle of “disease uncertainty → functional limitation → reinforced uncertainty” through a cascade of effects, such as impaired self-care abilities and social role disengagement [7] [11]. When patients perceive their illness as a “burden on the family,” the resulting negative emotional experiences—such as guilt—further exacerbate the emotional toll associated with uncertainty in illness [3]. Patients with unexplained fever experience a cycle of uncertainty that reinforces itself through “functional limitations” and “emotional distress,” trapping them in a vicious cycle of “uncertainty → deterioration → greater uncertainty.” Declining functionality exacerbates emotional suffering, while emotional issues further impede functional recovery, creating a self-perpetuating spiral.
This evidence suggests that helping patients reconstruct their cognitive framework regarding disease progression is crucial [16]. For instance, guiding patients to use symptom diaries to objectively record key information (e.g., fever frequency, examination milestones) aligns with Mishel’s core strategy in uncertainty in illness theory: enhancing “structural providers” to mitigate uncertainty [17].
4.2. The Moderating Role of Individual Cognitive and
Psychological Factors in Uncertainty
Illness uncertainty is a common negative psychological experience among patients with unexplained fever, closely linked to their cognitive functions and perceptual patterns. According to Mishel’s uncertainty in illness theory, an individual’s cognitive evaluation of illness-related stimuli serves as the precursor to uncertainty in illness. This process encompasses the individual’s ability to understand illness information, assess the severity of their condition, and satisfy their information needs [17].
A survey by Wang Yun et al. [9] of 162 patients with unexplained fever revealed that 30% exhibited high levels of uncertainty in illness due to insufficient medical knowledge and inadequate symptom interpretation abilities. Another comparative study [10] confirmed that when patients’ cognitive limitations prevent them from acquiring and processing effective disease information, their uncertainty in illness levels shows a positive correlation with the degree of information deficiency. This indicates that uncertainty in illness levels among patients with unexplained fever is significantly negatively correlated with disease cognition levels [18]. Factors such as symptom perception ambiguity and low educational attainment weaken patients’ ability to interpret test results, further intensifying their subjective experience of disease “unpredictability” [3].
Although most included quantitative studies focused on patients, caregiver uncertainty was also evident in the reviewed literature. A qualitative interview study exploring parents’ and doctors’ perspectives on the causes of pediatric FUO found that parents often struggled to interpret fever trajectories and to judge severity, while clinicians tended to frame the presentation using different causal explanations; this mismatch highlights caregiver uncertainty as an information-interpretation problem and underscores the need for aligned, family-centered communication [12]. In addition, a caregiver-focused discharge readiness intervention in a pediatric febrile condition assessed caregivers’ perceived uncertainty about the illness and reported improvements in the quality of discharge instructions and reductions in caregivers’ uncertainty following structured guidance [13]. Therefore, incorporating caregivers into key communication encounters (e.g., consistent explanations of diagnostic plans, expected course, and red-flag symptoms) and providing structured education may help reduce uncertainty at the family level [12] [13]. These findings suggest that optimizing the structure of information delivery and enhancing patients’ disease cognition represent potential intervention targets for alleviating uncertainty in illness [19].
Psychological factors serve as important moderators of uncertainty in illness. Research confirms [20] that high levels of uncertainty in illness often lead patients to adopt negative coping strategies, accompanied by heightened negative emotions. These negative emotions (anxiety, depression) may, in turn, diminish psychological resilience, thereby affecting treatment adherence and prognosis. A survey of patients with unexplained fever revealed that 85% experienced anxiety or depression, with their anxiety and depression scores showing a significant positive correlation with uncertainty in illness levels [3]. Fan Lingli et al. [7] demonstrated that personalized psychological interventions and health education for patients with moderate-to-severe anxiety and depression effectively reduced their uncertainty, alleviated negative emotions, and improved treatment adherence.
4.3. Socio-Demographic Characteristics and Economic Factors as
Key Predictors of Uncertainty
Previous studies [21]-[23] have confirmed that socio-demographic factors (e.g., age, educational attainment, marital status) and economic factors (e.g., household income, method of medical expense payment) are independent predictors of uncertainty in illness [22]-[24]. Results from multiple studies included in this review [3] [14] [25] [26] indicate that patients who are older (≥ 65 years), have lower educational attainment (primary school or below), lower monthly household income (< 3000 yuan), and unfavorable marital status (divorced/widowed) exhibit higher levels of uncertainty in illness.
Specifically, older patients often experience diminished capacity to receive and process information due to physiological decline and multiple coexisting conditions. Concurrently, the prolonged course of illness, involving repeated examinations, further erodes their sense of control over their disease [3] [26]. Patients with lower educational attainment possess relatively limited health literacy. This not only hinders their ability to independently access effective disease information but also increases susceptibility to misinterpreting healthcare providers’ explanations, trapping them in a cognitive dilemma of information deficiency and anxiety [3] [27] [28].
Economic pressure constitutes another core factor. Given FUO’s prolonged diagnostic cycle (median diagnosis time of 21 days) and high examination costs (accounting for 62% of household income), low-income patients often harbor concerns about substantial medical expenses. This financial burden may lead them to question treatment plans or delay decision-making, thereby intensifying feelings of uncertainty [3] [14] [25]. The moderating effect of marital status primarily manifests in emotional support. Divorced or widowed patients, lacking effective emotional guidance and support from intimate partners, may accumulate negative emotions, thereby intensifying their perception of uncertainty in illness [3]. Multiple studies included in this review also confirm that social support is a significant protective factor for uncertainty in illness, with high levels of social support helping to reduce patients’ uncertainty [11] [29] [30].
The above evidence suggests that clinical practice should identify patients with advanced age, low educational attainment, low income, and insufficient social support (e.g., divorced/widowed) as high-risk groups for uncertainty in illness and prioritize them for intervention. Establishing multidimensional social support systems—such as providing timely information support, fostering empathetic emotional environments (e.g., encouraging patients to express concerns and anxieties), and facilitating peer experience sharing—can effectively reduce patients’ levels of uncertainty in illness [24] [29] [30]. Furthermore, given the health literacy limitations of patients with low educational attainment, healthcare providers should use plain language supplemented with visual aids (e.g., images or models) when communicating about the condition. Care should be taken to avoid information overload to ensure effective communication [8] [11].
4.4. The Role of Information Needs and Physician-Patient
Communication in Uncertainty
Patients with unexplained fever exhibit multidimensional information needs, with a particularly pronounced demand for information regarding “disease progression and prognosis” [31]. Research indicates that healthcare providers’ failure to deliver clear, consistent disease information—such as explanations of examination procedures or the rationale for treatment plans—constitutes a significant iatrogenic factor contributing to uncertainty in illness [27]. Patient satisfaction with information fulfillment shows a significant negative correlation with uncertainty in illness levels [32]. When patients have limited cognitive capacity, their information needs are often harder to meet, thereby intensifying uncertainty in illness.
Insufficient communication and fragmented health education also exacerbate uncertainty in illness. Structured communication models, such as regular (e.g., weekly) condition summaries and one-on-one targeted education, have been proven effective in reducing information asymmetry and lowering uncertainty in illness levels [12] [33]. Furthermore, enhancing healthcare providers’ communication skills—particularly active listening and empathy—effectively increases information transparency and emotional support, serving as another effective pathway to reduce uncertainty in illness [7] [12].
4.5. Summary of Discussion
In summary, the emergence of disease uncertainty in patients with unexplained fever results from the interaction of multidimensional factors, including disease characteristics, individual cognition, psychological state, socioeconomic factors, and doctor-patient communication. Therefore, clinical nursing practice should establish a multimodal intervention system, integrating psychological support and information management into the routine care pathway for these patients. To establish a comprehensive inpatient management system, we have implemented an integrated pathway centered on structured assessment, encompassing evaluation, risk stratification, and tiered support. Initial screening and risk stratification are completed within 24 hours of admission. Within three days, high-risk patients undergo in-depth assessment and receive personalized intervention plans with tiered support. Dynamic reassessments occur throughout hospitalization, and follow-up plans are established prior to discharge, achieving closed-loop management from admission to discharge.
It is recommended to initiate dynamic assessments of uncertainty in illness and emotional states early in the diagnostic process. Based on these assessments, personalized health education and psychological interventions should be implemented to break the negative cycle of “information gap → rightarrow → negative emotions → rightarrow → heightened uncertainty,” thereby improving patients’ healthcare experiences and health outcomes [7] [13] [34] [35].
5. Conclusions
This systematic review confirms that uncertainty in illness among patients with unexplained fever is a complex psychological experience influenced by multiple interrelated factors. Key contributors include the unpredictability of disease progression, limitations in individual cognitive assessment (e.g., low health literacy), negative psychological states (e.g., anxiety, depression), adverse socio-demographic characteristics (e.g., advanced age, low income, low social support), and inadequate doctor-patient communication.
Therefore, clinical practice should integrate the assessment and management of uncertainty in illness into the standard care pathway for patients with unexplained fever. Dynamic evaluation should commence early in the diagnostic process, with enhanced information support and psychological interventions provided for high-risk groups characterized by advanced age, low educational attainment, low income, and insufficient social support [7] [13] [34] [35].
First, at intake (e.g., within 24 hours of admission or the first clinical encounter), nurses may administer a validated Uncertainty in Illness instrument (e.g., the Disease Uncertainty Scale / Illness Uncertainty Scale used in the included studies) to screen and stratify patients at high risk of elevated uncertainty. Second, uncertainty in illness should be reassessed at key diagnostic milestones (e.g., after major test result disclosures and prior to discharge), and patients with persistently high scores can be referred to a tiered support pathway—such as structured condition summaries, individualized education, and timely psychological support—to reduce uncertainty across hospitalization.
Limitations and Future Directions
This study also has limitations. Given that research on uncertainty in illness among patients with unexplained fever is still in its developmental stage, the retrospective literature review included a limited number of studies, most of which were cross-sectional, restricting inferences about causal relationships among various factors.
Future research should prioritize prospective longitudinal designs to elucidate the dynamic trajectories of uncertainty in illness and its causal associations with prognostic indicators. Concurrently, there is an urgent need to develop and validate interventions specifically targeting uncertainty in illness in patients with Fever of Unknown Origin, thereby providing evidence-based guidance for clinical practice.