心理学
心理健康
社会支持
感知组织支持
工作(物理)
服务(商务)
认知
公共关系
服务提供商
应用心理学
意外后果
社会分布认知
心理健康服务
社会认知理论
知识管理
社会心理学
组织文化
社会工作
组织变革
组织行为学
生产线管理
服务交付框架
高级管理人员
产业与组织心理学
员工敬业度
人力资源
医疗保健
业务
组织理论
作者
Nathan Black,Ekonkar Kaur,Misha Mariam,Christopher M. Barnes
标识
DOI:10.1177/01492063261433560
摘要
Social support is widely promoted as a key organizational response to employee mental health challenges, yet management research has often overlooked how different sources of support—such as coworkers, line managers, senior leadership, and professional service providers—vary in their effects on employee recovery. This oversight is especially consequential for employees managing common, diagnosable mental health conditions for whom recovery depends on changes in maladaptive cognitive and behavioral processes that are frequently activated in work contexts. To address this limitation, we conducted an interdisciplinary meta-synthesis of 96 review articles spanning management, clinical psychology, psychiatry, and occupational health. Anchored in Beck and Haigh’s Generic Cognitive Model, we develop the Integrated Work Support Model (IWSM), which explains how distinct sources of social support influence activating work situations, maladaptive beliefs, and maladaptive behaviors over time for employees with common mental health conditions. Our synthesis distinguishes the roles of primary, secondary, and tertiary interventions, clarifying when organizational actors can mitigate triggering work conditions, when clinical expertise from professional service providers is required to directly change maladaptive processes, and how social support from actors internal to the organization can enhance—but not substitute for—therapeutic intervention. By integrating clinical theory with management scholarship, this review advances a process-based understanding of social support, specifies role-differentiated responsibilities for organizational actors and professional service providers, and offers actionable guidance for designing social support systems that promote recovery while avoiding unintended harm.
科研通智能强力驱动
Strongly Powered by AbleSci AI