Nurses’ needs for digital mental health support: an analysis based on the Kano model

Objective: Nurses work under high pressure for a long time and are prone to anxiety, depression and other adverse emotions. Due to the nature of their work as well as time and space constraints, it is often difficult for them to pay attention to their own mental health problems in a timely manner. Digital mental health support can give nurses support to a certain extent and effectively relieve their stress. The aim of this study is to investigate and analyze nurses' demand for digital mental health support, to provide reference for the development of digital psychological interventions, and to provide a decision-making basis for the construction of a precise psychological support system and digital platform. Methods: This study employed the Kano model as an analytical tool to classify nurses' needs for digital mental health support. A cross-sectional survey was conducted with 1,571 nurses using a questionnaire developed through literature review and semi-structured interviews. The questionnaire included 26 items representing potential digital mental health features. For each item, participants answered paired functional and dysfunctional questions. Responses were classified into must-be, one-dimensional, attractive, and indifferent attributes using the standard Kano evaluation table. These demand attributes were then combined with the importance-satisfaction matrix to quantify the sensitivity of demand improvement. Results: Of the 26 needs, 8 were classified as must-be attributes, 8 as one-dimensional attributes, 7 as attractive attributes and 3 as indifferent attributes. Nurses rated the importance index of the digital mental health support demand items from -0.62 to -0.15, and satisfaction index from 0.34 to 0.62. Conclusion: The KANO model was applied to identify and categorize the different attributes of nurses' digital psychological support needs, offering targeted recommendations and strategies to address these needs, thereby providing a foundation for digital psychological interventions for nurses. Nursing managers can combine the results of Kano model analysis in the importance-satisfaction matrix to improve and satisfy nurses' demand for psychological support, so as to reduce their psychological pressure, improve job satisfaction, and lay the foundation for cultivating a high-level nursing team and promoting the high-quality development of nurses' career.

Authors

Institutions

Publication Details

Journal
Frontiers in Public Health
Published
2026-04-21
DOI
https://doi.org/10.3389/fpubh.2026.1796306
Primary Topic
Digital Mental Health Interventions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Nurses’ needs for digital mental health support: an analysis based on the Kano model

Ziyi Xiong, Huigen Huang, Le Chen, Tiemei Shen et al.
Frontiers in Public Health
Digital Mental Health Interventions
article

Nurses’ needs for digital mental health support: an analysis based on the Kano model

Ziyi Xiong, Huigen Huang, Le Chen, Tiemei Shen, Jiehao Zhuang, Xuanhao Fan, Zhanghao Xie, Z Chen, Peng Xu, Niu Yang
article en

Abstract

Objective: Nurses work under high pressure for a long time and are prone to anxiety, depression and other adverse emotions. Due to the nature of their work as well as time and space constraints, it is often difficult for them to pay attention to their own mental health problems in a timely manner. Digital mental health support can give nurses support to a certain extent and effectively relieve their stress. The aim of this study is to investigate and analyze nurses' demand for digital mental health support, to provide reference for the development of digital psychological interventions, and to provide a decision-making basis for the construction of a precise psychological support system and digital platform. Methods: This study employed the Kano model as an analytical tool to classify nurses' needs for digital mental health support. A cross-sectional survey was conducted with 1,571 nurses using a questionnaire developed through literature review and semi-structured interviews. The questionnaire included 26 items representing potential digital mental health features. For each item, participants answered paired functional and dysfunctional questions. Responses were classified into must-be, one-dimensional, attractive, and indifferent attributes using the standard Kano evaluation table. These demand attributes were then combined with the importance-satisfaction matrix to quantify the sensitivity of demand improvement. Results: Of the 26 needs, 8 were classified as must-be attributes, 8 as one-dimensional attributes, 7 as attractive attributes and 3 as indifferent attributes. Nurses rated the importance index of the digital mental health support demand items from -0.62 to -0.15, and satisfaction index from 0.34 to 0.62. Conclusion: The KANO model was applied to identify and categorize the different attributes of nurses' digital psychological support needs, offering targeted recommendations and strategies to address these needs, thereby providing a foundation for digital psychological interventions for nurses. Nursing managers can combine the results of Kano model analysis in the importance-satisfaction matrix to improve and satisfy nurses' demand for psychological support, so as to reduce their psychological pressure, improve job satisfaction, and lay the foundation for cultivating a high-level nursing team and promoting the high-quality development of nurses' career.

Frontiers in Public HealthVol. 14
Sun Yat-sen University (CN), Guangdong Pharmaceutical University (CN), Guangdong Academy of Medical Sciences (CN), Southern Medical University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 18%
Digital Mental Health Interventions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.