ArticleJMIR formative research2025
Assessing Work-Related Stressors in Online Counseling: Cross-Sectional Questionnaire Development Study.
Article in JMIR formative research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Digital Stress: Insights from Bibliometric, Scientometric, Meta-Analytic and Thematic Analyses.Healthcare (Basel, Switzerland) · 2026Review
- Impact of artificial intelligence and work digitalization on mental health and occupational well-being: a scoping review.Frontiers in public health · 2026Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The rapid digitalization of health and social services, particularly accelerated by the COVID-19 pandemic, has led to a widespread adoption of online counseling. While offering flexibility and improved access for clients, online counseling presents new challenges for counselors, including technical issues, difficulties in building therapeutic relationships, and changes in work organization. Despite growing reliance on digital counseling platforms, there is a lack of validated tools to assess specific occupational stressors associated with online counseling. Objective: This study aimed to develop and evaluate the "QueStrOn" (Questionnaire to Assess Stressors in Online Counseling), an instrument designed to identify stressors and resources specific to online counseling and to explore its ability to predict perceived stress levels in counselors. Methods: Item development was guided by the Job Demands-Resources model, qualitative interviews with 22 counselors, expert input, and a literature review. A preliminary version of the questionnaire was pretested and then distributed via email and social media to counselors offering both online and face-to-face services. A total of 219 counselors completed the survey, and after applying inclusion criteria, 174 responses were analyzed. Exploratory factor analysis was conducted using principal axis factoring and varimax rotation. Internal consistency was assessed via Cronbach alpha (α). A linear regression model was used to initially test the predictive power of the identified factors with perceived digital stress as the dependent variable. Results: The exploratory factor analysis resulted in a four-factor solution with 16 items, capturing (1) Online Work Organization, (2) Online Framework, (3) Online Work Content, and (4) Online Communication. The overall instrument demonstrated high internal consistency (α=0.870), with acceptable values for factors (1), (3), and (4) (α=0.754, 0.745, and 0.826, respectively), although the factor "Online Framework" showed limited reliability (α=0.502). The regression model, adjusted for age and gender, significantly predicted perceived stress in online counseling (F5=13.335, P<.001), explaining 27.1% of the variance. Online Work Organization, Online Communication, and Online Framework were associated with lower perceived stress when rated positively, whereas Online Work Content showed an inverse relationship, potentially reflecting emotional distancing. Conclusions: The QueStrOn instrument provides a valid first step toward systematically assessing occupational stressors in online counseling. Its 4-factor structure aligns with theoretical and empirical findings and offers practical utility for workplace risk assessments. Incorporating these dimensions into routine evaluations may support counselor well-being and inform digital health policy. Further validation and longitudinal studies are recommended to expand its applicability and explore associations with broader health outcomes.
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