Development and Validation of a Dual-Language (English and Malay) Needs Assessment Tool for Breast Cancer (NeAT-BC).

Asia breast cancer development needs assessment questionnaire validation

Journal

Diagnostics (Basel, Switzerland)
ISSN: 2075-4418
Titre abrégé: Diagnostics (Basel)
Pays: Switzerland
ID NLM: 101658402

Informations de publication

Date de publication:
09 Jan 2023
Historique:
received: 03 11 2022
revised: 16 12 2022
accepted: 05 01 2023
entrez: 21 1 2023
pubmed: 22 1 2023
medline: 22 1 2023
Statut: epublish

Résumé

Background: Needs assessment tools may be used to guide the optimisation of cancer survivorship services. We sought to develop and validate a dual-language needs assessment tool for women with breast cancer. Methods: The study comprised two phases; (I) co-design, and (II) psychometric testing. In Phase I, items were generated based on focus group discussions with patients and a literature review. These items were then translated into the Malay language. Content and face validation were undertaken with an expert panel. In phase II, 315 Malaysian women living with breast cancer were recruited. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted to determine construct validity and reliability. Criterion validity was assessed using the EORTC QLQ-C30 questionnaire. Results: We co-designed and validated a 48-item dual-language needs assessment tool for breast cancer (NeAT-BC). Five underlying constructs were revealed in the EFA: (1) emotional support, (2) social and intimate relationships, (3) hospital appointments, (4) personal care and health, and (5) information and services. The NeAT-BC demonstrated good reliability across all constructs (Cronbach’s alpha: 0.90 to 0.96). CFA also demonstrated acceptable convergent and divergent validity, composite reliability ≥ 0.87, and Heterotrait−Monotrait index < 0.85 for all constructs. Criterion validity was established given the significant negative correlation between overall needs and quality of life (r = −0.14; p = 0.02). The NeAT-BC took approximately 25 min to be completed and could be interviewer-administered or self-administered. Conclusion: The utilization of the NeAT-BC is expected to guide establishment of evidence-based cancer survivorship services in Malaysia, with wider potentials for adoption in other multi-ethnic and/or low-and-middle income settings.

Identifiants

pubmed: 36673050
pii: diagnostics13020241
doi: 10.3390/diagnostics13020241
pmc: PMC9858119
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Ministry of Higher Education
ID : IIRG006C-19HWB
Organisme : Pfizer Malaysia
ID : UPUM/2019-MED.316

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Auteurs

Yek-Ching Kong (YC)

Department of Social and Preventive Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia.

Mahmoud Danaee (M)

Department of Social and Preventive Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia.

Ranjit Kaur (R)

Breast Cancer Welfare Association Malaysia, Petaling Jaya 46200, Malaysia.

Muthukkumaran Thiagarajan (M)

Department of Radiotherapy and Oncology, Kuala Lumpur Hospital, Kuala Lumpur 50586, Malaysia.

Hafizah Zaharah (H)

Department of Radiotherapy and Oncology, National Cancer Institute, Putrajaya 62250, Malaysia.

Mustafa Sener (M)

Department of Social and Preventive Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia.
Erasmus University Medical Centre, 3015 GD Rotterdam, The Netherlands.

Harenthri Devy Alagir Rajah (HDA)

Department of Social and Preventive Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia.

Nur Aishah Taib (NA)

Department of Surgery, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia.

Karuthan Chinna (K)

Faculty of Business and Management, UCSI University, Kuala Lumpur 56100, Malaysia.

Cheng-Har Yip (CH)

Subang Jaya Medical Centre, Subang Jaya 47500, Malaysia.

Nirmala Bhoo-Pathy (N)

Department of Social and Preventive Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia.

Classifications MeSH