Decision-Making Readiness in Chemotherapy-Treated Lung Cancer Patients

When a patient sits across from an oncologist and hears that chemotherapy is recommended for lung cancer, the moment that follows is rarely a simple yes or no. It is the culmination of a complex psychological process involving how well the person understands the disease, how confident they feel about weighing options, how supported they perceive themselves to be, and how prepared they are to live with the consequences of the choice they make. A new cross-sectional study from China, published in the open-access journal Nursing Open, has now measured that preparedness directly in one of the largest single-cohort investigations of its kind, and the results suggest that most hospitalized lung cancer patients receiving chemotherapy are only moderately ready to take part in the treatment decisions that will shape their lives. The findings carry practical weight for clinicians worldwide, because they indicate that the strongest levers for improving patient readiness are not demographic characteristics but modifiable psychosocial states, particularly the degree of internal conflict a patient feels and the attitude that patient holds toward participating in decisions at all.

The research team, working in the oncology department of a specialized cancer hospital in Beijing, recruited 452 hospitalized adults with pathologically confirmed lung cancer who were actively receiving chemotherapy between August and October 2024. The choice of population was deliberate. Lung cancer remains the most commonly diagnosed malignancy worldwide, and China alone reported more than one million new cases and roughly 740,000 deaths in 2022, making it the country’s leading cause of cancer-related morbidity and mortality. Chemotherapy in lung cancer is not confined to advanced disease; it is deployed as neoadjuvant and adjuvant therapy across the disease trajectory, which means patients face repeated, recurring treatment decisions rather than a single dramatic choice at diagnosis. Each cycle brings fresh opportunities to continue, modify, or abandon a regimen, and each of those junctures demands a fresh assessment of risks, side effects, functional impact, and financial cost. Unlike some cancers where a one-time surgical decision dominates, lung cancer imposes a rolling sequence of choices on patients who are often emotionally depleted, physically weakened, and cognitively taxed by rapid disease progression.

To quantify readiness, the researchers employed the Chinese version of the Preparation for Decision Making Scale, a ten-item instrument originally developed by Canadian nursing scholars and later revised by Bennett and colleagues, psychometrically validated in Chinese by Li Yu. Items are rated on a five-point Likert scale, and the total score, obtained by multiplying the summed item scores by four, ranges from 20 to 100, with higher values indicating greater readiness. In the current sample the scale demonstrated strong internal consistency, with a Cronbach’s alpha of 0.903. The median readiness score among the 452 participants was 62.00, with an interquartile range of 56.00 to 70.00, which the authors characterize as a moderate overall level. In practical terms, this means that the typical patient in the study reported being reasonably but not robustly prepared to engage in treatment decision-making, leaving substantial room for improvement in a population where inadequate decision preparation has previously been linked to higher decisional conflict, lower satisfaction, and poorer treatment adherence.

The study’s analytical backbone was a hierarchical multiple linear regression grounded in the Common Sense Model of Self-Regulation, a classic theoretical framework in health psychology that describes how individuals confronting a health threat form cognitive and emotional representations of the illness, adopt coping behaviors in response, and then evaluate outcomes. The researchers mapped this framework onto the decision-making context: the cognitive stage was captured by measures of decision-making attitude, decisional conflict, and decisional regret, while the coping outcome was embodied in the overall level of decision-making readiness. Attitude was measured with the Chinese version of the Patient Attitude Toward Treatment Decision-Making Scale, a twelve-item instrument developed by Sainio and colleagues and validated in Chinese by Ma Lili. Decisional conflict was assessed with the sixteen-item Decisional Conflict Scale developed by O’Connor, which spans three dimensions—clarity of information and values, perceived decision support and effectiveness, and decisional uncertainty—with scores above 25 indicating the presence of conflict and scores above 37.5 suggesting possible decision delay. Decisional regret was measured with the five-item Decision Regret Scale of Brehaut and colleagues, although its internal consistency in this sample was low, with a Cronbach’s alpha of 0.401, and the authors caution that regret-related findings should be interpreted with appropriate restraint.

The statistical results were striking in their proportions. In the first block of the regression, sociodemographic and clinical contextual variables—factors such as economic status and residential location—explained 9.2 percent of the total variance in decision-making readiness. When the psychological variables of decisional conflict and participation attitude were added in the second block, the explanatory power jumped to 31.1 percent, more than tripling the variance accounted for. Four factors emerged as significant independent predictors: economic status, residential location, decisional conflict, and decision participation attitude. Correlation analysis reinforced the pattern, showing that readiness was positively associated with patients’ willingness to participate in treatment decisions and negatively associated with decisional conflict. Collinearity diagnostics confirmed that the psychological predictors were not redundant, with variance inflation factors ranging from 1.197 to 1.409, well below conventional thresholds of concern. In plain language, the study found that how a patient feels about deciding matters far more than who the patient is.

This asymmetry between demographic and psychosocial predictors is arguably the study’s most consequential message. Economic status and residential location, while statistically significant, are largely fixed or slowly changing features of a patient’s life that clinicians cannot readily modify at the bedside. Decisional conflict and participation attitude, by contrast, are psychological states that can be assessed, monitored, and targeted with structured interventions. Decision aids, teach-back communication techniques, question prompt lists, and dedicated nursing decision-support consultations are all evidence-informed tools designed to reduce uncertainty, clarify values, and bolster confidence. The finding that these modifiable variables explain a substantial share of readiness variance offers a concrete roadmap: screening patients for decisional conflict at admission could identify those at greatest risk of unprepared decision-making, and tailored support could then be deployed before critical treatment junctures arrive.

The study also fills a notable gap in the oncology literature. Prior research on treatment decision-making in cancer has concentrated heavily on negative indicators—decisional conflict, decisional regret, and dissatisfaction with the decision process—while giving comparatively little attention to decision-making readiness as an independent, positive, adaptive psychological construct. Readiness, as the authors define it, encompasses the comprehensive preparedness of an individual in knowledge, attitude, ability, and environmental support when facing a decision situation, enabling effective participation and informed choice. Moreover, much of the existing work has been descriptive, lacking an organizing theoretical framework to explain how readiness forms. By anchoring the analysis in the Common Sense Model of Self-Regulation and demonstrating that the model’s cognitive and coping stages map coherently onto measurable decision-related variables, the researchers provide both empirical data and a theoretical scaffold that future intervention studies can build upon. The authors note that their findings support the applicability of the Common Sense Model in the field of cancer treatment decision-making research more broadly.

The clinical context adds urgency to these numbers. A traditionally paternalistic approach in thoracic oncology has been recognized as a barrier to shared decision-making, and patients whose decisions are made entirely by family members—still a common practice in some health systems—were excluded from this study precisely to focus on those expected to participate themselves. Even among this engaged cohort, readiness was only moderate. The authors point out that lung cancer patients may face greater decisional complexity than patients with many other cancer types, driven by rapid disease progression, high emotional distress at the time of diagnosis, and limited time to absorb and process information. When the window between diagnosis and a consequential treatment choice is measured in days rather than weeks, the quality of decision support delivered in that window becomes decisive, and a patient who enters it with unresolved internal conflict and a passive attitude toward participation is at a measurable disadvantage.

Methodologically, the study was carefully sized and executed. Following the rule that no fewer than ten participants are required per predictor variable, twenty-five candidate predictors demanded a minimum of 250 participants; anticipating a 20 percent invalid-questionnaire rate raised the floor to 313, and the final sample of 452 comfortably exceeded it. Data were collected through structured electronic questionnaires administered by trained research nurses, with each device permitted a single submission, standardized instructions for every section, and an average completion time of approximately fifteen minutes. Patients with psychiatric histories or severe cognitive impairment, those too ill to continue chemotherapy, and those unaware of their diagnosis were excluded. Analyses were conducted in SPSS version 26.0, with Shapiro-Wilk tests for normality, appropriate parametric and non-parametric comparisons, and two-tailed significance testing throughout. The researchers are transparent about the design’s cross-sectional nature, which captures association rather than causation, and about convenience sampling at a single specialized hospital, which may limit generalizability to community settings or to patients managed outside major urban cancer centers.

Even with those caveats, the implications for nursing practice and oncology care are difficult to ignore. The authors conclude that targeted nursing decision-support interventions are urgently needed to assess and elevate decision-making readiness among lung cancer patients receiving chemotherapy, as a pathway toward genuinely patient-centered treatment decision-making. The idea that readiness can be measured with a short, reliable, validated scale—and that its principal modifiable determinants are conflict and attitude rather than age, education, or disease stage—transforms an abstract ideal of shared decision-making into an operational clinical target. As oncology systems worldwide push toward greater patient involvement, this study suggests the critical question is not simply whether patients are invited to the table, but whether, when they arrive, they arrive prepared.