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 Table of Contents  
Year : 2022  |  Volume : 13  |  Issue : 1  |  Page : 10

Assessment of intraorganizational collaboration in the health sector during disasters: Exploring a valid and reliable assessment tool for disaster risk management

1 National Emergency Medical Organization, Ministry of Health & Medical Education, Tehran, Iran
2 Department of Health in Disasters and Emergencies, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
3 Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
4 Department of Health in Disasters and Emergencies, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences; Air Quality and Climate Change Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Date of Submission16-Dec-2020
Date of Acceptance24-May-2021
Date of Web Publication19-Jan-2022

Correspondence Address:
Sanaz Sohrabizadeh
Air Quality and Climate Change Research Center, Shahid Beheshti University of Medical Sciences, Tehran
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijpvm.IJPVM_696_20

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Background: Collaboration, as a key factor in disaster risk management, is a mechanism that prevents the loss of time, investment, and resources. The variety of units in the health sector has made collaboration a major challenge. The present study aimed at developing a tool for assessing collaboration in the health sector during disasters. Methods: In this mixed-methods study, a questionnaire was developed by integrating the findings of a systematic literature review and a qualitative study. Face and content validation were performed. The reliability of the tool was tested through a 15-day interval test–retest by Cronbach's alpha and intraclass correlation coefficient (ICC) with 30 participants. Confirmatory factor analysis was done to test the validity and reliability of instrument using SmartPLS in a case study with 450 health sector staff. Results: The factors affecting intraorganizational collaboration of the health sector were identified in six categories and 19 subcategories by searching 46 articles in the systematic review and content analysis of 16 semistructured interviews with health sector staff. The results of content validity ratio (=0.81), content validity index (=0.92), Cronbach's alpha (=0.975), and ICC (=0.970) confirmed the validity and reliability of the tool. Convergent validity, discriminant validity, and reliability were approved by AVE (average variance extracted) >0.5, Fornell and Larcker matrix, and CR (composite reliability) >0.7. According to the positive result of R2, Q2, and goodness-of-fit (GOF) criteria, the model fit was confirmed. Conclusion: The results of validity and reliability measurements approved the proposed tool. The use of this tool is recommended for developing collaboration in the health sectors of different countries.

Keywords: Disaster planning, disasters, health care sector, intersectoral collaboration, natural disasters, surveys and questionnaires

How to cite this article:
Yousefian S, Jahangiri K, Mehrabi Y, Sohrabizadeh S. Assessment of intraorganizational collaboration in the health sector during disasters: Exploring a valid and reliable assessment tool for disaster risk management. Int J Prev Med 2022;13:10

How to cite this URL:
Yousefian S, Jahangiri K, Mehrabi Y, Sohrabizadeh S. Assessment of intraorganizational collaboration in the health sector during disasters: Exploring a valid and reliable assessment tool for disaster risk management. Int J Prev Med [serial online] 2022 [cited 2022 Oct 3];13:10. Available from: https://www.ijpvmjournal.net/text.asp?2022/13/1/10/335965

  Introduction Top

Natural disasters have been affecting societies and causing serious damages to human life and health.[1] The frequency of natural disasters and their consequences, such as death, injuries, and financial losses has been increasing over the years.[2] After the occurrence of disasters, different services are essential for responding to the needs and compensating for the damages, and health systems play a critical role in providing services to the first and most important demands of the affected people.[1],[3] Population displacement, high-density settlements, and weak response to basic health needs create a situation that endangers people's health in disasters.[4] The health sector with the liability of the Ministry of Health and Medical Education (MOHME) takes necessary measures to help the health system respond to disasters.[5] Therefore, all stakeholders in the health sector should be well prepared to provide compatible, integrated, accessible, and coordinated services to reduce mortality, morbidity, and injuries, and increase the number of survivors.[1],[6],[7],[8],[9]

The concept of collaboration in disasters refers to the close relationships of units whose services are required at the time of disasters so that all of them are aware of their duties and collaborate to achieve a common goal. Collaboration as a key factor of disaster risk management success,[10] is a mechanism that prevents the loss of time, investment, and resources in disasters.[8],[11] The variety of different units and departments in the health sector, including the providers of prehospital services, public health services, curative, and rehabilitation services, as well as information management centers, safety and security centers, and planning and policy-making centers has made collaboration more difficult especially in disasters.[7],[9],[12],[13],[14],[15],[16] Lack of collaboration as an important challenge in the health sector has resulted in the disruption of tasks and parallel work and has prevented the procurement of suitable services in disasters.[8],[9],[14],[15],[17],[18],[19],[20] Given that the issue has been rarely studied[8],[15],[17],[18],[19],[21],[22],[23] and the focus of studies is more on the collaboration between different responsible organizations, evaluating the collaboration function can help the health sector by identifying and eliminating obstacles and problems of partnerships and improve future collaborations in disasters.[15] Despite the difficulty of evaluation in terms of different operational measures, indicators, and accountability systems,[24],[25] the use of collaboration assessment results can lead to effective disaster response through improved collaboration.[26] Therefore, when designing and developing collaboration mechanisms, evaluation of this important managerial function using suitable tool and criteria should be considered.[24],[27]

Totally, a valid and reliable assessment tool can help identify deficits and the domains that need to be changed[28],[29] and provide accurate data for improving policies and plans.[30] For filling this gap, the present study aimed to design and validate a tool for assessing intraorganizational collaboration of the health sector in disaster management that can lead to improving collaboration among subunits of the health sector during disasters.

  Methods Top

Study Design

A mixed-methods approach was applied for conducting the study between April 2019 and September 2020 in three stages in Iran's MOHME. The study was planned in three phases – systematic review, qualitative study for designing the tool, and a quantitative study for achieving reliability and validity criteria.

Designing primary tool

Systematic review

This stage was done for identifying the factors affecting intraorganizational collaboration of health sector in disasters management. During this stage, categories, subcategories, and appropriate items were identified and generated through searching in Scopus, Web of Science, MEDLINE (PubMed), ProQuest, Google Scholar, Scientific Information Database, and key journals. To include as many studies as possible, broad search terms were used: (“coordination,” “collaboration,” “cooperation”), (“intra-agency,” “intra-organizational,” “intra-sectional,” “intra-sectoral”), (“model,” “framework,” “theoretical framework,” “model,” “conceptual framework”), (“disasters,” “natural disaster,” “hazards”) and (“health system,” “health sector,” “public health sector,” “health service,” “healthcare service”). These groups were combined with “AND” together and were looked up in selected databases. The studies related to effective factors on health sector collaboration in disasters management were searched from January 2000 to May 2019.

After removing all duplicates, the evaluation of studies was performed by the title and abstract screening and the inclusion criteria by two researchers. Finally, 46 eligible studies were included, and the full text of the selected articles was analyzed independently by two researchers considering the inclusion and exclusion criteria and standard quality assessment. In the case of disagreement in the selection of studies, a third person was the final decision maker to include them.

The data extraction sheet was designed regarding each study's information, including title, purpose, the name(s) of author(s), the year of publication, the data source, journal's name, the type of study, and study findings. And also all extracted data were evaluated by the research team to verify the accuracy and completeness.

Qualitative study

Qualitative content analysis with a deductive approach based on Bryson's model[31] was carried out to develop the model and to identify the components and factors influencing the success of intraorganizational collaboration in the context of Iran.

The participants of the qualitative stage were 16 managers and experts of MOHME and Emergency Medical Organization who had the experience of working in the field of disasters. All participants were selected by a purposive sampling method. We communicated with the units and departments of MOHME and Emergency Medical Organization to identify the participants and their experiences. Subsequently, the main criteria to choose the eligible employees included having at least 5 years of work experience in the health sector, having field-based experience in a natural disaster with a focus on earthquakes and floods, and having the willingness to participate in the interview. The number of participants was determined based on the saturation principles until no new concepts were developed.

We conducted semistructured interviews for data collection and extracting the experience of participants. The interview guide was provided with several questions and supplemented with complementary questions during interview sessions. Each interview session lasted between 20 and 60 minutes. Informed consent was obtained from the interviewees for recording the interviews. All interviews were recorded and transcribed verbatim in Persian. Data gathering and analysis were performed simultaneously such that the retrieved information became a guide for further data collection.

The analysis took a deductive approach to discover the factors affecting health sector collaboration from the perspective of participants. All interviews were read several times to obtain a sense of the whole. The units of analysis were selected, and then meaning units were formed by extracting the text. The next step was labeling the condensed meaning units with a code. Finally, comparing the extracted codes with regard to their differences and similarities and grouping them into categories and subcategories formed the first draft of the collaboration assessment tool in disasters.

The trustworthiness of our study was assessed using four criteria.[32] Credibility was approved via the triangulation strategy. In addition to interviews, prolonged engagement with the subject provided credibility. Moreover, peer checks were conducted in research team meetings and member checks were done by providing a summary of the analyzed interviews and extracted codes to the participants. Conformability of the data was accomplished by the lead researcher. Transferability of data was confirmed by offering a comprehensive description of the subject, participants, data gathering, and data analysis. Dependency was assured through the current article, which offers detailed information for other researchers to replicate and extend the study.

Measuring validity and reliability

Quantitative study

The findings of the qualitative study and the systematic review were used to design the primary tool and to remove the duplicated factors. At this stage, face validity, content validity, and reliability were measured.

Validity: The validity of the proposed questionnaire was assessed as follows:

  • Face validity

    Face validity was measured by sending the questionnaire to 15 experts (including managers and experts of MOHME, universities, and Emergency Medical Organization) and receiving their overall conception in responding to all the items. For face validity, an impact score was computed through a 5-point Likert-type scale, in which the response”very important” was scored as 5 and the response “it is not important at all” was scored as 1. The impact score was obtained by multiplying the item's frequency (the percentage of responses with the important score of 4 or 5) and item's importance (importance of each item on a 5-point Likert-type scale). The cutoff point to select the items was calculated as 1.5, and the items with a value less than 1.5 were removed.[33],[34]

  • Content validity

    Content validity was measured through the content validity ratio (CVR) and content validity index (CVI) criteria. In this study, 15 specialists in the field of health in disasters were selected to carry out the content validation forms. To calculate the CVR, each specialist determined the “necessity of each item” in the questionnaire by selecting one of the three options “not essential,” “useful but not essential,” or “essential,” and based on their ideas, the score of each item was determined from 1 to 3, respectively. Then using the equation related to this topic and considering the number of participants and the participants who selected the option “essential,” the CVR for each item was calculated. According to the Lawshe table that was used in this phase,[35] the acceptable CVR score was 0.49, and the items with scores less than 0.49 were removed.

    The CVI was another approach for determining the content validity of the tool. So, in this stage, the questionnaire was sent to 15 experts, and all of them were requested to rate the tool items in terms of relevancy, simplicity, and clarity based on a 4-point scale and to select the score of each item from 1 to 4. For calculating the CVI, the number of experts who gave a score of 3 or 4 to each item was divided by the total number of experts. The items with scores higher than 79% were accepted, and the items with scores between 70% and 79% were revised.[36]

    Reliability: Assessment of the external consistency of the tool was performed using test–retest method. This process was carried out with the participation of 30 health sector personnel with a 15-day interval between the two stages of test and retest. For every participant, the whole score was calculated at both the test and retest stages. Then the intraclass correlation coefficient (ICC) was calculated for the two scores to determine if there was a significant relationship between the responses in the two stages. With regard to 95% confident interval of the ICC estimation, the results of the calculation were interpreted based on the following classification: 0.0–0.2 (low), 0.21–0.40 (fair), 0.41–0.60 (moderate), 0.61–0.80 (substantial), and 0.81–1.0 (almost perfect).[33]

Model evaluation

In the final stage, a survey was conducted to generate the data for confirmatory factor analysis. The designed tool was distributed between the managers and experts of MOHME, Emergency Medical Organization, and 18 universities. The random sampling approach was used for data sampling. The acceptable sample size was estimated at 450 by considering five samples per each item.[33] After collecting the distributed tool, the data were entered into SmartPLS software. The measurement model of the study was assessed by determining its reliability and validity, and the structural model was assessed using Q2, R2, and goodness of fit (GOF).

The reliability of the measurement model was established using the composite reliability (CR), factor loading, and Cronbach's alpha (α). Cronbach's alpha and CR values above 0.7 were considered desirable. The validity of the measurement model was determined using both convergent validity and discriminant validity. Convergent validity was determined by average variance extracted (AVE) recommended values, and an AVE value above 0.50 was accepted. The measurement model's discriminant validity was determined using the Fornell and Larcker matrix.

R2 was used to assess the explanatory power of the research model, and the predictive capability of the model was evaluated using Stone–Geisser's Q2 for endogenous constructs of the study. Both the criteria and GOF values above 0 were considered desirable.[37]

  Ethical Approval and Consent to Participate Top

This study was approved by the Ethics Committee of Shahid Beheshti University of Medical Sciences, Tehran, Iran (IR.SBMU. PHNS. REC.1397.112). All participants entered the study with their own written consent, and they were allowed to leave the project at any phase of the study. Besides, the participants were informed about the confidentiality of their private information in related reports.

  Results Top

Systematic review

In the first stage of this study in which a systematic review was carried out, the full texts of 157 out of 5,889 extracted studies were examined, and 46 eligible studies were included. By analyzing the selected studies, intraorganizational collaboration of the health sector in disasters was classified into six categories: initial conditions, collaborative structures, collaborative processes, facilitating factors, conflicts and tensions, and accountabilities and outcomes, which were classified into 16 subcategories.[38]

Content analysis

The qualitative stage of the study was conducted with 16 participants. The participants of this stage were in the age range of 32 and 50 years. Furthermore, 69% were male and 31% were female [Table 1]. Six categories and 19 subcategories were extracted from the data at this stage [Table 2].
Table 1: Demographic Information of Participants (Qualitative Study)

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Table 2: Categories and Subcategories Extracted From Qualitative Data

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Antecedent Conditions: This category with five sections reflects various issues as the initial conditions of collaboration in any organization. These factors facilitate collaboration by influencing the collaborative processes and structures.

Structural Factors: The collaborative structure is another important factor influencing the success of collaboration. This category reflects the necessity of integrated structures in disaster risk management; determining the tasks, roles, and responsibilities of all stakeholders; and describing power and authority relationships by defining decision-making and accountability paths.

Process Factors: This category focuses on building trust, communication, executive capacity, and planning. Collaborative processes help partners establish collaborative structures and vice versa, so the processes and structures have to be related to fostering collaboration.

Facilitating Factors: The existence of facilitators or drivers is essential for the success of the collaboration. The most important facilitators are leadership and technology.

Disincentives Factors: Tensions and conflicts within the organization can affect collaborative processes and structures. These organizational constraints are generally influenced by organizational culture.

Accountabilities and Outcomes: Types of assessments in the effective management of disasters; functional accountability; and individual, organizational, and social consequences are the main subjects of this category.

Design and validation of the tool

At the stage of designing the intraorganizational collaboration tool in disaster, all categories and subcategories extracted from the previous two stages were checked out, and 154 items were extracted. The items were reviewed by the research team, and the repetitious and overlapping items were removed. The first version of the questionnaire was developed by selecting 110 items on six dimensions.

  • Face and content validity

    To determine content validity in the first round, CVR and CVI were computed for each question as well as for the whole tool by sending the tool to 15 specialists. Based on the Lawshe table, 17 items were removed because their CVR scores were less than 0.49. The total CVR (average of CVRs of all items) for the whole tool was 0.81. In the round of calculating the CVI, no question was removed. However, some questions with scores between 70% and 79% were revised. The overall scale's content validity (S-CVI) was measured to be 0.92.

    To determine face validity, the tool was given to 15 employees familiar with the topic and who held responsible positions in the secretariat of the Health Policy Council in Disaster and in the Emergency Operation Centers (which are the centers of coordination and control of response operations in MOHME and medical universities). They were asked to judge the importance of each item, and based on their opinion the impact score of the items was calculated. According to the comments received, a few items needed to be revised, and seven items with a score less than 1.5 were removed. Eventually, after assessing the face and content validity of the tool, 88 items in six dimensions remained [Table 3]. In the final tool, a 5-point Likert-type scale was used (very high = 5, high = 4, medium = 3, low = 2, and very low = 1).

  • Reliability

    The stability of the tool was computed by ICC. In this stage, the average measure ICC was 0.970 with a 95% confidence interval from 0.952 to 0.984, which indicated desirable reliability of the tool. Besides, the reliability of the tool was measured with Cronbach's alpha for all dimensions and total items. The estimated Cronbach's alpha was 0.975, which fully confirms the internal consistency of the questionnaire. Cronbach's alpha and ICC of the six dimensions and the total tool are shown in [Table 4].
Table 3: Results of Validity and Reliability Measurements

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Table 4: Cronbach's Alpha and Interclass Correlation (ICC) of Dimensions and Total Questionnaire

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Measurement model evaluation

The results of descriptive statistics showed that most of the participants were female, in the age range of 36 to 45 years, having master's degree and above, and had more than 15 years of work experience [Table 5]. The examination of factor loading showed that the values of this indicator for question No. 56 in the structural factors, question No. 63 in the process factors, and question No. 80 in the disincentives factors were lower than 0.3, and were removed[39] [Figure 1] and the final questionnaire was accepted with 85 items [appendix]. The T-value in all items was greater than 2.58; this indicated that all factor loadings at the 99% confidence interval level were positive and meaningful [Figure 2].
Table 5: Demographic Information of Participants (Quantitative Study)

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Figure 1: Variance, factor loading, and path coefficient

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Figure 2: T-statistics by executing a bootstrapping procedure

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Cronbach's alpha values and CR were greater than 0.7, which indicate a high reliability of the questionnaire.

Convergent validity was measured by the average variance extracted (AVE). The results showed that the measurement model of the current study had sufficient convergent validity because AVE values for all the variables were above the recommended values of 0.50 [Table 6]. The instrument in this study had good discriminant validity because each square root of AVE is larger than the correlation of the latent variables and the factor loading is a group in the same column [Table 7].
Table 6: Reliability, Convergent Validity, and Fitness Criterion

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Table 7: Discriminant Validity of Measurement Model: Fornell and Larcker Criterion

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The results of the model fit showed that R2 is acceptable and the independent variables have been able to explain the changes of the dependent variable to an acceptable level. Also, positive values of the Q2 showed that the model has the power to predict relationships and the high-degree of GOF criterion approves the fit of the model [Table 6].

  Discussion Top

This study developed a tool for assessing the intraorganizational collaboration function as the most important challenge of the health sector in disaster management. The current tool that is extracted from a mixed-methods study considered six dimensions, which include antecedent conditions, structural factors, process factors, facilitating factors, disincentives factors, and accountabilities and outcomes. The validity and reliability of the tool indicate that the tool is accurate enough for intraorganizational collaboration assessment in disaster management.

A systematic and comprehensive approach was considered in developing the tool. This approach could help identify, clarify, and understand the concept, antecedents, and consequences of collaboration deeply and also facilitate its improvement.[8],[30],[31],[40],[41],[42] A deep understanding of the concept of collaboration by health care providers results in an improvement in resource allocation, quality of service delivery, and people's health situation during disasters.[9] So the present tool with 85 questions in six categories, all input, process, and output factors was considered and confirmed. The results of the calculations showed that the relationship between all six main factors with collaboration was positive and significant.

The initial conditions of collaboration can strongly affect the formation of collaborations. Having related and supportive policies and regulations; collaborative culture[11],[31]; successful collaboration experiences[26]; the stakeholders' agreement on their mission, goals, policies, programs, values, problems, and their solutions[23],[43],[44]; and access to resources such as financial, human, physical, and information[45] are essential and preconditions of a successful collaboration.

Clarifying collaborative processes as another factor affecting collaboration requires plans and standard protocols.[46] Besides planning, communication and building trust are important factors of the collaborative process because these can reduce the complexity and transaction costs faster than other factors.[8],[26],[31],[47],[48],[49],[50]

Due to various times for response to different health needs of people affected by disasters, the health sector should make clear the roles and responsibilities of each department in the various phases of disaster management.[9] The transparency in collaboration structure (horizontal and vertical) and the roles and responsibilities based on it can reduce confusion among groups involved and improve collaboration.[46],[48]

Facilitating factors such as committed and powerful leaders and technology can facilitate collaboration.[31] On the other hand, tensions and conflicts can affect the collaborative process negatively and hinder the success of the partnership. Therefore, the use of appropriate conflict management methods such as regular meetings to raise and resolve problems will be helpful.[31],[47]

Accountability and outcome are other factors affecting the success of the collaboration. The main subject in examining the accountability of providers and the consequences of collaboration is monitoring and evaluation, which play important role in identifying obstacles and problems, eliminating and preventing their recurrence, and increasing collaboration in future disasters.[15] Collaboration improvement using the results of collaboration assessment and outcomes like any reform effort in the health systems requires the support, participation, and commitment of all stakeholders.[30],[31],[42],[44],[45] The importance of this issue is such that its existence or nonexistence determines the success or failure of collaboration,[28] so it should be considered as a vital factor.

Monitoring and evaluating collaboration with the use of a suitable tool can help the health sector by identifying the current situation of collaboration and the strengths and weaknesses in disaster participatory management.[26],[28] The results of the collaboration assessment create an opportunity to strengthen capacities, remove barriers, and prevent recurrence of inconsistencies in future disasters.[8],[15],[23] In this situation, it will be possible to provide an effective response and achieve the common goals.[48],[51]

The research team encountered some limitations in each stage of the study. In the qualitative stage, the experiences of the participants in natural disasters with a focus on earthquakes and floods were extracted. The current tool has been developed in the Persian language and then translated into English. Thus, translation validity should be conducted by researchers who are not Persian speaking.

  Conclusions Top

The results of content validity and reliability measurements show that the current tool can be applied for analyzing the situation of pre and post disaster collaboration in the health sector. Considering the impact of various factors on intraorganizational collaboration in disasters, a comprehensive tool with a systematic approach that can be easily applied by policymakers, managers, and health care providers was designed. Although the current tool was developed for the health sector in Iran's context, health systems in other countries with similar structure and sociocultural context can apply this tool in disaster management. The use of the information provided by this tool is highly recommended for developing and revising policies, goals, strategies, and programs of the health sector in disaster risk management. Furthermore, the intraorganizational collaboration analysis tool can be used in all phases of disaster management, including mitigation, preparedness, and response. Further research is needed to identify the associations between factors affecting the success of intraorganizational collaboration and to modify the current tool.


The authors thank all the participants of this study for their genuine cooperation.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

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  [Figure 1], [Figure 2]

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]


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