Abstract
Purpose
Families raising autistic children usually experience daily difficulties, such as accommodating their children’s unique communication patterns and behavioral expressions. Despite these potential challenges, families can demonstrate resilience by showing effective family functioning. However, research on the factors that may influence family resilience in this population remains limited. This meta-analysis aims to identify and synthesize the risk and protective factors associated with family resilience among families with autistic children.
Methods
We conducted a systematic review of studies based on six online English databases (PubMed, PsycINFO, Embase, Web of Science, MEDLINE, and Scopus) and two Chinese databases (CNKI and Wanfang). Combined Pearson correlations were calculated by using the random effects model. A moderator analysis was conducted to explore the impact of moderators such as the study region and study quality. The risk of bias and publication bias were also evaluated.
Results
Forty-one studies were examined, where 15 risk and protective factors were identified. Among the 15 factors, 12 are intrapersonal factors (e.g., parental self-efficacy, parental stress, etc.), and 3 are interpersonal factors (social support, family cohesion, and family quality of life).
Discussion
Our findings indicate that the strongest correlations with family resilience were observed among interpersonal factors. In addition, we identified a number of salient (e.g., family cohesion) and contextually unique (e.g., uncertainty about autism) risk and protective factors for family resilience. Building on this, we propose a multi-level family resilience conceptual framework that can inform targeted interventions for families raising autistic children.
Trial registration
This study was registered with PROSPERO (No: CRD42024595923).
Families raising autistic children usually experience daily difficulties, such as accommodating their children’s unique communication patterns and behavioral expressions. Despite these potential challenges, families can demonstrate resilience by showing effective family functioning. However, research on the factors that may influence family resilience in this population remains limited. This meta-analysis aims to identify and synthesize the risk and protective factors associated with family resilience among families with autistic children.
Methods
We conducted a systematic review of studies based on six online English databases (PubMed, PsycINFO, Embase, Web of Science, MEDLINE, and Scopus) and two Chinese databases (CNKI and Wanfang). Combined Pearson correlations were calculated by using the random effects model. A moderator analysis was conducted to explore the impact of moderators such as the study region and study quality. The risk of bias and publication bias were also evaluated.
Results
Forty-one studies were examined, where 15 risk and protective factors were identified. Among the 15 factors, 12 are intrapersonal factors (e.g., parental self-efficacy, parental stress, etc.), and 3 are interpersonal factors (social support, family cohesion, and family quality of life).
Discussion
Our findings indicate that the strongest correlations with family resilience were observed among interpersonal factors. In addition, we identified a number of salient (e.g., family cohesion) and contextually unique (e.g., uncertainty about autism) risk and protective factors for family resilience. Building on this, we propose a multi-level family resilience conceptual framework that can inform targeted interventions for families raising autistic children.
Trial registration
This study was registered with PROSPERO (No: CRD42024595923).
| Original language | English |
|---|---|
| Number of pages | 27 |
| Journal | BMC psychology |
| DOIs | |
| Publication status | E-pub ahead of print - 16 Jul 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
User-Defined Keywords
- Autism spectrum disorder
- family resilience
- risk/protective factors
- meta-analysis
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