Evidence map›Paper›PMID 42215288›Full record

Observational studyJournal of clinical nursing2026

Dyadic Coping and Its Influencing Factors in Patients With Prostate Cancer Undergoing Androgen Deprivation Therapy and Their Spouses: A Latent Class Analysis.

Haishan Chen, Yamei Li, Hua He, Haihang Lin, Xinyue Song, Kun Li

Abstract readObservational StudyReview
In one paragraph

Observational study in Journal of clinical nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Haishan ChenDepartment of Urology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Yamei LiDepartment of Urology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Hua HeDepartment of Urology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Haihang LinDepartment of Urology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Xinyue SongDepartment of Urology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Kun LiSchool of Nursing, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-0092-7178

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AIM(S): To identify distinct dyadic coping patterns among prostate cancer patients undergoing androgen deprivation therapy and their spouses using a person-centred approach, and to explore factors associated with these patterns to inform the development of personalised interventions.

designA cross-sectional, observational study design.

methodsA total of 223 patient-spouse dyads were recruited from two tertiary urology departments in Guangdong Province, China, between October 2024 and August 2025. All participants completed a general information questionnaire and the Dyadic Coping Inventory. Latent profile analysis was used to identify distinct coping profiles. Univariate analysis and multivariate logistic regression were performed to examine factors associated with profile membership.

resultsAmong 223 patient-spouse dyads, four distinct dyadic coping profiles were identified: Efficient Coping (12.0%), Ambivalent Coping (30.0%), Stable Coping (53.8%), and Coping Distress (4.0%). The small Coping Distress subgroup (n = 9) was excluded from further analysis. Higher dyadic coping levels were associated with patient education of high school or above, absence of tumour recurrence, sufficient patient-perceived family support, low-to-moderate spouse-perceived medical burden, frequent dyadic communication, and sufficient spouse-perceived friend/colleague support. Spouse-perceived insufficient family support was unexpectedly associated with better dyadic coping.

conclusionDyadic coping patterns among prostate cancer patients undergoing androgen deprivation therapy and their spouses are heterogeneous. Healthcare professionals should identify distinct dyadic coping characteristics and provide personalised nursing interventions based on the key influencing factors identified in this study. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: This study provides a person-centred classification framework for dyadic coping in couples undergoing androgen deprivation therapy, enabling nurses and other healthcare professionals to deliver targeted, stratified psychosocial care. Early identification of vulnerable couples, particularly those in the ambivalent coping subgroup, helps prevent maladaptive coping and alleviate psychological distress. By addressing modifiable factors including communication, family support, and caregiver burden, clinical practice can more effectively improve the psychosocial well-being and quality of life of both patients and their spouses throughout androgen deprivation therapy. REPORTING

methodThis study adheres to the relevant EQUATOR guidelines (STROBE) for cross-sectional studies. PATIENT OR PUBLIC CONTRIBUTION: Patients and their spouses were involved in the design of the study by providing feedback on the clarity and relevance of the questionnaire items during a pilot phase. They also participated in data collection by completing the self-report measures, and their input informed the interpretation of the findings related to dyadic coping experiences.

Indexed as

Adaptation, PsychologicalAndrogen AntagonistsProstatic NeoplasmsSpousesAgedChinaCoping SkillsCross-Sectional StudiesFemaleHumansLatent Class AnalysisMaleMiddle AgedSurveys and QuestionnairesAndrogen Antagonistsandrogen deprivation therapydyadic copinglatent profile analysisprostate cancerspouses

Identifiers

PMID42215288
PMCPMC13432284

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.