Using Social Media Platforms to Raise Health Awareness and Increase Health Education in Pakistan: Structural Equation Modeling Analysis and Questionnaire Study
Bibliographic record
Abstract
Background: Current health care education methods in Pakistan use traditional media (eg, television and radio), community health workers, and printed materials, which often fall short of reach and engagement among most of the population. The health care sector in Pakistan has not yet used social media effectively to raise awareness and provide education about diseases. Research on the impact social media can have on health care education in Pakistan may expand current efforts, engage a wider audience, and reduce the disease burden on health care facilities. Objective: This study aims to evaluate the perceptions of health care professionals and paramedic staff regarding social media use to raise awareness and educate people about diseases as a potential means of reducing the disease burden in Pakistan. Methods: The study used two-stage structural equation modeling (SEM). Data analysis used AMOS 26.0 software, adopting scales from previous literature. Four-item scales for each social media usefulness and health awareness construct and 8-item scales for health care education constructs were adopted on the basis of their higher loading in alignment with psychometric literature. A 7-point Likert scale was used to measure each item. Data collection used convenience sampling, with questionnaires distributed to more than 450 health care professionals and paramedic staff from 2 private hospitals in Lahore, Pakistan. There were 389 useful responses received. However, 340 completed questionnaires were included in the data analysis. Results: The study found that all the squared multiple correlation (SMC) values were greater than 0.30. Furthermore, convergent validity was measured using (1) standardized factor loading (found greater than 0.5), (2) average variance explained (found greater than 0.5), and (3) composite reliability (found greater than 0.7). The confirmatory factor analysis (CFA) of the measurement model indicated the fitness of the constructs (Chi-square minimum [CMIN]=357.62; CMIN/degrees of freedom [DF]=1.80; Goodness of Fit [GFI]=0.90; Adjusted Goodness of Fit Index [AGFI]=0.89; Buntler-Bonett Normed Fit Index [NFI]=0:915; Comparative Fit Index [CFI]=0:93; Root Mean Square Residual [RMR]=0:075; Root Mean Square Error of Approximation [RMSEA]=0:055). Moreover, the structural model fitness was also confirmed (CMIN=488.6; CMIN/DF=1.85; GFI=0.861; AGFI=0.893; NFI=0.987; CFI=0.945; RMR=0:079; RMSEA=0.053). Hence, the results indicated that social media usefulness has a positive and significant effect on health awareness (hypothesis 1: β=.669, P<.001), and health awareness has a positive and significant effect on health care education in Pakistan (hypothesis 2: β=.557, P<.001). Conclusions: This study concludes that health care professionals and paramedic staff in private hospitals support the use of social media to raise awareness and provide health care education. It is considered an effective tool for reducing the disease burden in Pakistan. The study results also revealed that young health care professionals are more inclined toward social media usage and express the need for legislation to support it and establish a monitoring process to avoid misinformation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".