Evidence map›Paper›PMID 38699099›Full record

ArticleCureus2024

Effectiveness of Tailor-Made Physiotherapy Protocol in Smartphone-Addicted Individuals With Text Neck Syndrome and Short Message Service (SMS) Thumb.

Harsh R Nathani, Pratik Phansopkar

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Harsh R NathaniMusculoskeletal Physiotherapy, Ravi Nair Physiotherapy College, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Pratik PhansopkarMusculoskeletal Physiotherapy, Ravi Nair Physiotherapy College, Datta Meghe Institute of Higher Education and Research, Wardha, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Smartphone usage has led to an increase in text neck syndrome (TNS) and short message service (SMS) thumb, causing neck, shoulder, and thumb pain, affecting daily activities. Limited treatment options are available for these conditions, and early intervention is crucial to prevent chronic pain and musculoskeletal issues. This study sought to determine the impact of a personalized physiotherapy treatment plan on alleviating TNS and SMS thumb in individuals who demonstrate excessive smartphone usage. Method The study utilized a single-group, pre- and post-study design with a sample size of 54 smartphone-addicted individuals. The intervention involved a personalized physiotherapy protocol for three weeks, and data was collected using a visual analog scale (VAS), Neck Disability Index (NDI), Smartphone Addiction Scale (SAS), Cornell Hand Discomfort Questionnaire (CHDQ), and range of motion (ROM). Results Descriptive statistics showed a significant reduction in mean scores from pre- to post-rehabilitation, indicating the potential effectiveness of the treatment. Hypothesis testing revealed significant improvements in VAS, NDI, and CHDQ scores post-rehabilitation, with a p-value of <0.05. Correlation analysis demonstrated moderate to strong correlations between pre- and post-rehabilitation scores for VAS, NDI, and CHDQ, with age showing minimal influence on treatment outcomes. Conclusion The findings emphasize the efficacy of personalized interventions in addressing smartphone-related musculoskeletal disorders and underscore the need for further research to optimize treatment protocols and long-term outcomes.

Indexed as

musculoskeletal disorderspain managementpersonalized treatmentphysiotherapysmartphone addictionsmartphone usagesms thumbtext neck syndrome

Identifiers

PMID38699099
PMCPMC11064880

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.