Integration of Disaster Risk Reduction (DRR) and Climate Change Adaptation (CCA) is gaining popularity to address the increasing threat of climate change. People living in high disaster-prone impoverished areas can benefit from risk reduction interventions and subsequent adaptation of new technologies and behavior if those interventions diminish the perceived risk of disaster. Perceived risk of disaster plays an important role in influencing adaptive behavior. Disaster risk reduction interventions therefore can be benefitted from inclusive local consultation during the planning and implementation of the risk reduction interventions by taking local people's perceived risk of disaster into account. We studied a national-level disaster risk reduction program called ‘The comprehensive Disaster Management Program (CDMP)’ in Bangladesh to understand the linkage between risk reduction interventions, perceived risk of disaster, and adaptation. Following a mixed-method approach, we collected quantitative administrative data, interviewed local people, and conducted Focus Group Discussions in two disaster-prone neighboring coastal unions of Bangladesh. We have found that if risk reduction interventions designed by the central government are not aligned with the perceived risk of the local people, the implementation of these interventions does not reduce perceived risk significantly, and consequently, people do not adopt new technologies and behavior to increase their resilience to climate change shocks. Furthermore, people's valuation of a risk reduction intervention in reducing the perceived risk of disasters does not change after an actual disaster takes place insinuating the relative accuracy and robustness of local people's assessment of such interventions. We also found that risk reduction interventions implemented in a holistic way addressing multiple sources of risks can reduce perceived risk significantly. Lastly, we demonstrated that reducing perceived risk is a necessary condition but is not sufficient to encourage adaptation. Our study can contribute to improving the design and implementation of large-scale risk-reduction interventions implemented at the community level.