| Literature DB >> 25295667 |
Gareth Furber1, Gabrielle Margaret Jones, David Healey, Niranjan Bidargaddi.
Abstract
BACKGROUND: Few studies have tested whether individually tailored text messaging interventions have an effect on clinical outcomes when used to supplement traditional psychotherapy. This is despite the potential to improve outcomes through symptom monitoring, prompts for between-session activities, and psychoeducation.Entities:
Keywords: eHealth; mHealth; mental health services; mobile health; psychotherapy; short message service; telemedicine
Mesh:
Year: 2014 PMID: 25295667 PMCID: PMC4210953 DOI: 10.2196/jmir.3096
Source DB: PubMed Journal: J Med Internet Res ISSN: 1438-8871 Impact factor: 5.428
Figure 1Flow of participants into the intervention group.
Figure 2Flow of participants into the historical control group.
Intake status, attendance, and clinical outcomes for the intervention and control groups.
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| Intervention group (n=45) | Control group (n=157) | Difference | Comparisons |
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| Age at assessment, mean (SD) | 34.1 (14.5) | 37 (15.8) | −3.51 (−8.7 to 1.67) |
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| Gender, n (%) male | 15 (33.3) | 68 (43.3) | −10% | χ2 1=1.44 |
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| Employment, n (%) employed | 22 (48.9) | 68 (43.3) | 5.6% | χ2 1=0.44 |
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| Relationship, n (%) yes | 18 (40.0) | 44 (28.0) | 12% | χ2 1=2.12 |
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| High school complete, n (%) yes | 20 (44.4) | 64 (40.8) | 3.6% | χ2 1=2.28 |
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| Prescribed psychotropic medication, n (%) yes | 24 (53.3) | 113 (72) | −18.7% | χ2 1=6.02 |
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| Chronic health condition, n (%) yes | 13 (28.9) | 55 (35.0) | −6.1% | χ2 1=0.44 |
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| Treatment completers, n (%) | 28 (62.2) | 111 (70.7) | −8.5% | χ2 1=1.17 |
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| Treatment length in days, mean (SD) | 43.3 (17.1) | 46.3 (26.7) | −3.05 (−11.74 to 5.64) |
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| Number of sessions, mean (SD) | 3.73 (1.9) | 4.43 (2.3) | −0.700 (−1.44 to 0.04) |
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| Number of DNAa, mean (SD) | 1.42 (1.12) | 1.76 (1.51) | −0.342 (−0.82 to 0.14) |
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| PHQbPre, mean (SD) | 19.4 (6.4) | 18.9 (5.6) | 0.480 (−1.46 to 2.42) |
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| GADcPre, mean (SD) | 16.1 (5.2) | 15.8 (4.4) | 0.350 (−1.18 to 1.88) |
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| WSASdPre, mean (SD) | 27.7 (9.8) | 27.0 (10.0) | 0.730 (−0.26 to 4.06) |
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| PHQ Post, mean (SD) | 6.64 (6.23) | 7.57 (6.85) |
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| GAD Post, mean (SD) | 5.41 (5.51) | 6.81 (6.17) |
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| WSAS Post, mean (SD) | 10.89 (10.70) | 12.49 (12.44) |
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aDNA: did not attend
bPHQ: Patient Health Questionnaire
cGAD: Generalized Anxiety Disorder questionnaire
dWSAS: Work and Social Adjustment Scale
Figure 3Proportion of intervention and control participants by number of sessions attended.
Post hoc power analyses for number of sessions attended and PHQascores.
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| Number of sessions attended | PHQ scores |
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| Post hoc: Compute achieved power | Post hoc: Compute achieved power |
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| Tail(s)=Two | Effect size |
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| Effect size | α err prob=0.05 |
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| α err prob=0.05 | Total sample size=203 |
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| Sample size group 1=157 | Number of groups=2 |
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| Sample size group 2=45 | Number of measurements=2 |
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| Correlation among repeated measures=0.257 |
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| Nonsphericity correction ε=1 |
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| Noncentrality parameter δ=1.9675292 | Noncentrality parameter λ=2.7458948 |
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| Critical | Critical |
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| df=200 | Numerator df=1.0000000 |
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| Power (1-β err prob)=0.4992920 | Denominator df=201 |
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| Power (1-β err prob)=0.3781274 |
aPHQ: Patient Health Questionnaire