Factors influencing utilization of school health nurse program among secondary students of Lalitpur, Nepal: a mixed-method study.
Acknowledging the unique health needs of school children, the Government of Nepal launched the "One School One Nurse" initiative, which was first implemented by the Provincial Government of Bagmati Province in 2018/2019. The program aims to improve health outcomes among school children by deploying a certified nurse in community schools who provides preventive healthcare, health education and first-aid services. Though the program is being scaled up over provinces, it is in its initial stage of development and there are scarce published literature available about the program. This limited availability of comprehensive resources evaluating the program's usage and supportive and hindering factors demands further investigation on it. Thus, this study assessed the utilization of school nurse services among secondary students and identified the factors associated with service utilization quantitatively. Also, the study explored the underlying factors influencing school nurse service utilization qualitatively. Finally, the study did the triangulation to cross-validate the findings from both quantitative and qualitative studies.
A concurrent triangulation mixed-method study was conducted in six public schools randomly selected from each of six local levels of Lalitpur district implementing the ''One school one nurse'' program. Quantitative data were collected from 280 students in grades 9-12 using a self-administered questionnaire. Qualitative data were gathered through in-depth interviews with ten students and key informant interviews with six school staff including school nurses and teachers. Data collection was done from November 2022 to January 2023. Quantitative data were analyzed using weighted multivariable logistic regression to determine predictors of school nurse service utilization. For the qualitative component, a deductive approach based on the socioecological framework was employed to explore factors influencing service utilization.
The school nurse service utilization rate among secondary students was 28.69% in Lalitpur. The odds of utilizing the service were two times higher among students below 16 years (AOR: 2.08, 95% CI: 1.07-4.02) compared to older students. Additionally, those motivated by teachers, school nurses and parents had four times higher odds of utilization of the service (AOR: 4.16, 95% CI: 1.26-13.64) compared to those without such external encouragement. Conversely, students having learning difficulties had about 68% lower odds of utilizing the school nurse service (AOR: 0.316, CI:0.134-0.744) compared to the student without such difficulties. Triangulation of findings from both studies revealed factors like age, sex, External motivation, student awareness about services and learning difficulty influenced service utilization. Moreover, frequent turnover of school nurses, their absence in school during their training sessions or external programs and insufficient coordination between provincial, local, and school authorities significantly hindered students' access to services. Ethical approval for the study was obtained by the Institutional Review Committee of Patan Academy of Health Sciences (Ref: PHP2209301678).
Around one third of secondary students utilized the school nurse services in past one year in Lalitpur district. Enhancing awareness and motivation among students, with a particular focus on older students, male students, and those with learning difficulties, could help increase service utilization rates. Additionally, implementing better staffing strategies and strengthening coordination among stakeholders would enhance program effectiveness, ultimately leading to improved service access. Further research is recommended to examine factors that positively or negatively impact the program at a broader level, incorporating insights from divisional and local level authorities.
Sharma S
，Mahotra A
，Thapa TR
，Thapa P
，Bhandary S
，Bhushal S
，Paudel S
... -
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A New Measure of Quantified Social Health Is Associated With Levels of Discomfort, Capability, and Mental and General Health Among Patients Seeking Musculoskeletal Specialty Care.
A better understanding of the correlation between social health and mindsets, comfort, and capability could aid the design of individualized care models. However, currently available social health checklists are relatively lengthy, burdensome, and designed for descriptive screening purposes rather than quantitative assessment for clinical research, patient monitoring, or quality improvement. Alternatives such as area deprivation index are prone to overgeneralization, lack depth in regard to personal circumstances, and evolve rapidly with gentrification. To fill this void, we aimed to identify the underlying themes of social health and develop a new, personalized and quantitative social health measure.
(1) What underlying themes of social health (factors) among a subset of items derived from available legacy checklists and questionnaires can be identified and quantified using a brief social health measure? (2) How much of the variation in levels of discomfort, capability, general health, feelings of distress, and unhelpful thoughts regarding symptoms is accounted for by quantified social health?
In this two-stage, cross-sectional study among people seeking musculoskeletal specialty care in an urban area in the United States, all English and Spanish literate adults (ages 18 to 89 years) were invited to participate in two separate cohorts to help develop a provisional new measure of quantified social health. In a first stage (December 2021 to August 2022), 291 patients rated a subset of items derived from commonly used social health checklists and questionnaires (Tool for Health and Resilience in Vulnerable Environments [THRIVE]; Protocol for Responding to and Assessing Patient Assets, Risks and Experiences [PRAPARE]; and Accountable Health Communities Health-Related Social Needs Screening Tool [HRSN]), of whom 95% (275 of 291; 57% women; mean ± SD age 49 ± 16 years; 51% White, 33% Hispanic; 21% Spanish speaking; 38% completed high school or less) completed all items required to perform factor analysis and were included. Given that so few patients decline participation (estimated at < 5%), we did not track them. We then randomly parsed participants into (1) a learning cohort (69% [189 of 275]) used to identify underlying themes of social health and develop a new measure of quantified social health using exploratory and confirmatory factor analysis (CFA), and (2) a validation cohort (31% [86 of 275]) used to test and internally validate the findings on data not used in its development. During the validation process, we found inconsistencies in the correlations of quantified social health with levels of discomfort and capability between the learning and validation cohort that could not be resolved or explained despite various sensitivity analyses. We therefore identified an additional cohort of 356 eligible patients (February 2023 to June 2023) to complete a new extended subset of items directed at financial security and social support (5 items from the initial stage and 11 new items derived from the Interpersonal Support Evaluation List, Financial Well-Being Scale, Multidimensional Scale of Perceived Social Support, Medical Outcomes Study Social Support Survey, and 6-item Social Support Questionnaire, and "I have to work multiple jobs in order to finance my life" was self-created), of whom 95% (338 of 356; 53% women; mean ± SD age 48 ± 16 years; 38% White, 48% Hispanic; 31% Spanish speaking; 47% completed high school or less) completed all items required to perform factor analysis and were included. We repeated factor analysis to identify the underlying themes of social health and then applied item response theory-based graded response modeling to identify the items that were best able to measure differences in social health (high item discrimination) with the lowest possible floor and ceiling effects (proportion of participants with lowest or highest possible score, respectively; a range of different item difficulties). We also assessed the CFA factor loadings (correlation of an individual item with the identified factor) and modification indices (parameters that suggest whether specific changes to the model would improve model fit appreciably). We then iteratively removed items based on low factor loadings (< 0.4, generally regarded as threshold for items to be considered stable) and high modification indices until model fit in CFA was acceptable (root mean square of error approximation [RMSEA] < 0.05). We then assessed local dependencies among the remaining items (strong relationships between items unrelated to the underlying factor) using Yen Q3 and aimed to combine only items with local dependencies of < 0.25. Because we exhausted our set of items, we were not able to address all local dependencies. Among the remaining items, we then repeated CFA to assess model fit (RMSEA) and used Cronbach alpha to assess internal consistency (the extent to which different subsets of the included items would provide the same measurement outcomes). We performed a differential item functioning analysis to assess whether certain items are rated discordantly based on differences in self-reported age, gender, race, or level of education, which can introduce bias. Last, we assessed the correlations of the new quantified social health measure with various self-reported sociodemographic characteristics (external validity) as well as level of discomfort, capability, general health, and mental health (clinical relevance) using bivariate and multivariable linear regression analyses.
We identified two factors representing financial security (11 items) and social support (5 items). After removing problematic items based on our prespecified protocol, we selected 5 items to address financial security (including "I am concerned that the money I have or will save won't last") and 4 items to address social support (including "There is a special person who is around when I am in need"). The selected items of the new quantified social health measure (Social Health Scale [SHS]) displayed good model fit in CFA (RMSEA 0.046, confirming adequate factor structure) and good internal consistency (Cronbach α = 0.80 to 0.84), although there were some remaining local dependencies that could not be resolved by removing items because we exhausted our set of items. We found that more disadvantaged quantitative social health was moderately associated with various sociodemographic characteristics (self-reported Black race [regression coefficient (RC) 2.6 (95% confidence interval [CI] 0.29 to 4.9)], divorced [RC 2.5 (95% CI 0.23 to 4.8)], unemployed [RC 1.7 (95% CI 0.023 to 3.4)], uninsured [RC 3.5 (95% CI 0.33 to 6.7)], and earning less than USD 75,000 per year [RC 2.7 (95% CI 0.020 to 5.4) to 6.8 (95% CI 4.3 to 9.3)]), slightly with higher levels of discomfort (RC 0.055 [95% CI 0.16 to 0.093]), slightly with lower levels of capability (RC -0.19 [95% CI -0.34 to -0.035]), slightly with worse general health (RC 0.13 [95% CI 0.069 to 0.18]), moderately with higher levels of unhelpful thoughts (RC 0.17 [95% CI 0.13 to 0.22]), and moderately with greater feelings of distress (RC 0.23 [95% CI 0.19 to 0.28]).
A quantitative measure of social health with domains of financial security and social support had acceptable psychometric properties and seems clinically relevant given the associations with levels of discomfort, capability, and general health. It is important to mention that people with disadvantaged social health should not be further disadvantaged by using a quantitative measure of social health to screen or cherry pick in contexts of incentivized or mandated reporting, which could worsen inequities in access and care. Rather, one should consider disadvantaged social health and its associated stressors as one of several previously less considered and potentially modifiable aspects of comprehensive musculoskeletal health.
A personalized, quantitative measure of social health would be useful to better capture and understand the role of social health in comprehensive musculoskeletal specialty care. The SHS can be used to measure the distinct contribution of social health to various aspects of musculoskeletal health to inform development of personalized, whole-person care pathways. Clinicians may also use the SHS to identify and monitor patients with disadvantaged social circumstances. This line of inquiry may benefit from additional research including a larger number of items focused on a broader range of social health to further develop the SHS.
Brinkman N
，Broekman M
，Teunis T
，Choi S
，Ring D
，Jayakumar P
... -
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ResearchGate
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