Background: There was an increasing attention to the humanization of oncological cares that focused on patients’ needs – which have a strong impact on quality of life. Cancer-related needs seem to be related both to physical, practical and psychological difficulties as well as gender and age. Using a Latent Class Analysis (LCA) the aim of the study was to identify a latent structure accounting for the covariance between cancer-related needs. A one-factor model with two classes was hypothesized, which comprised needs as indicators and difficulties as external variables that moderate the latent structure. Methods: Patients (N = 171, 50.3% female, mean age = 64.6, SD = 12.7) were enrolled at the Department of Medical Oncology, “Presidio Ospedaliero” of Saronno, ASST Valle Olona, Italy. Using a standardized checklist patients were tested for physical issues, practical problems and distress (Psychological Distress Inventory: PDI; α = .88). Then, patients were tested with the Need Evaluation Questionnaire (NEQ) measuring: (A) communicative (α = .78) and (B) relational needs (α = .74); needs of information related to (C) the diagnosis (α = .72) and (D) treatments (α = .70). Results: A CFA was performed to confirm the original factorial structure of the NEQ (RMSEA = .059; CFI = .913) and the PDI (RMSEA = 0.72; CFI = .902). Then, the LCA (5000 bootstrap) shows the goodness-of-model fit [χ2 (6) = 9.06; p = .17; LRχ2 (6) = 10.64; p = .10] and the goodness-of-classification quality [Entropy = .84 ( > .7); Average-Latent-Class-Assignment-Probability: .950 and .964 for Class1 and Class2, respectively]. The LCA identified a latent variable with two classes (VLMR = 161.33; p < .001; Class1 = .54%; Class2 = .46%). In addition, interactions with the latent variable were found only for distress (β = .892; p = .019), practical (β = 1.26; p = .010) and physical (β = .983; p = .012) issues. Conclusions: These results provide a better understand of cancer-related needs: each class represents a specific “profile” that are moderated by physical, practical and psychological difficulties. These findings suggest paying more attention to the specific need expressed by the patient proposing new ways to improve quality of life.

Profiling cancer-related needs and the role of physical, practical and psychological difficulties: A latent class analysis approach

Rossi, A
Conceptualization
;
Mannarini, S;
2018

Abstract

Background: There was an increasing attention to the humanization of oncological cares that focused on patients’ needs – which have a strong impact on quality of life. Cancer-related needs seem to be related both to physical, practical and psychological difficulties as well as gender and age. Using a Latent Class Analysis (LCA) the aim of the study was to identify a latent structure accounting for the covariance between cancer-related needs. A one-factor model with two classes was hypothesized, which comprised needs as indicators and difficulties as external variables that moderate the latent structure. Methods: Patients (N = 171, 50.3% female, mean age = 64.6, SD = 12.7) were enrolled at the Department of Medical Oncology, “Presidio Ospedaliero” of Saronno, ASST Valle Olona, Italy. Using a standardized checklist patients were tested for physical issues, practical problems and distress (Psychological Distress Inventory: PDI; α = .88). Then, patients were tested with the Need Evaluation Questionnaire (NEQ) measuring: (A) communicative (α = .78) and (B) relational needs (α = .74); needs of information related to (C) the diagnosis (α = .72) and (D) treatments (α = .70). Results: A CFA was performed to confirm the original factorial structure of the NEQ (RMSEA = .059; CFI = .913) and the PDI (RMSEA = 0.72; CFI = .902). Then, the LCA (5000 bootstrap) shows the goodness-of-model fit [χ2 (6) = 9.06; p = .17; LRχ2 (6) = 10.64; p = .10] and the goodness-of-classification quality [Entropy = .84 ( > .7); Average-Latent-Class-Assignment-Probability: .950 and .964 for Class1 and Class2, respectively]. The LCA identified a latent variable with two classes (VLMR = 161.33; p < .001; Class1 = .54%; Class2 = .46%). In addition, interactions with the latent variable were found only for distress (β = .892; p = .019), practical (β = 1.26; p = .010) and physical (β = .983; p = .012) issues. Conclusions: These results provide a better understand of cancer-related needs: each class represents a specific “profile” that are moderated by physical, practical and psychological difficulties. These findings suggest paying more attention to the specific need expressed by the patient proposing new ways to improve quality of life.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/3278632
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