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Earthquake stressful events cause many consequences and need for survivors. Housing reconstruction is one of the most urgent needs; due to traumatic experiences, dialectical changes in people–place relationships occur.

The present study uses the Poe method and Q methodology to identify the hidden dimensions of trauma-informed housing reconstruction. A questionnaire with 74 items on the Likert scale was developed based on indicative Poe. It was completed by the purposive sampling method by Bam households. The influential factors in housing reconstruction with a psychological recovery approach were extracted by q-factor analysis in communities with different traumatic experiences.

According to the findings, first, people who had experienced complete home destruction; severe physical injuries; loss of family members and relatives; and were trapped under the earthquake rubble have different place-based needs in housing reconstruction for coping with fears and environmental concerns, protective behaviors, safety perception and as result safety reassurance. Second, regardless of the traumatic experience and losses, reconstruction acceleration and economic-social dignity have a positive effect on the communities’ psychological recovery.

It is noteworthy that housing reconstruction with a psychological recovery approach has two basic aspects. Although some independent factors of traumatic experiences will be efficient in this approach, it was found that the type of earthquake traumatic experiences will also be effective in the survivors’ place-based needs and biases.

This study examined the role of artificial intelligence (AI) tools in facilitating the accessibility and usability of electronic resources (e-resources) in academic libraries.

This study employed a quantitative descriptive survey to collect data from library users. The population targeted was sampled using a purposive sampling technique. A total of 427 (58%) participated in this study.

Most respondents preferred electronic journals (e-journals) among the e-resources stored in academic libraries. Chatbots were identified as preferred AI tools for accessing and enhancing the usability of these resources. Strategies mentioned included the potential for integrating AI tools across various e-resources. However, among the challenges reported was the inability to integrate AI tools with the existing library management systems. Improving e-resource discovery and access can significantly enhance the effectiveness of AI tools in academic libraries.

Originality in the context of AI applications in academic libraries refers to the unique approaches, innovative tools and creative solutions that enhance the accessibility and usability of electronic resources. By focusing on unique solutions that enhance the accessibility and usability of e-resources, these libraries can better serve their diverse user populations and adapt to the evolving landscape of information needs.