Help‐Seeking Stage of Change Measure

2020 ◽  
Author(s):  
Oliver G. Johnston ◽  
Olivia J. Derella ◽  
Melanie A. Gold ◽  
Jefrey D. Burke
2019 ◽  
Vol 49 (2) ◽  
pp. 223-246
Author(s):  
Oliver G. Johnston ◽  
Olivia J. Derella ◽  
Melanie A. Gold ◽  
Jeffrey D. Burke

2008 ◽  
Vol 38 (1) ◽  
pp. 27-37
Author(s):  
Lucy E. Napper ◽  
Catherine M. Branson ◽  
Dennis G. Fisher ◽  
Grace L. Reynolds ◽  
Michelle M. Wood

2004 ◽  
Vol 94 (1) ◽  
pp. 115-124 ◽  
Author(s):  
Christopher L. Cook ◽  
Matthew Perri

The Stage of Change construct from the Transtheoretical Model of behavioral change has been widely utilized in the assessment of various health behaviors. The majority of these tests measure the Stage of Change construct using the single-item, multiple-choice format. This study validated the use of a single-item measure in measuring readiness to comply with taking a prescribed medication. A sample of 161 subjects tested the multiple-item Stage of Change measure, then a refined multiple-item survey was tested with 59 subjects. With the latter survey, discriminating subjects at the differing stages of change dimensions was difficult. A correlation of .91 was found for stage classifications between ratings on the single-item and multiple-item scales. The use of the single-item measure seems reasonable when assessing stage of change in compliance with prescribed medication.


2003 ◽  
Author(s):  
Stacey L. Stevens ◽  
Brian Colwell ◽  
Katherine Miller ◽  
Donald Sweeney ◽  
Catherine McMillan ◽  
...  

Author(s):  
E. O. D. Waygood ◽  
Bobin Wang ◽  
Ricardo A. Daziano ◽  
Zachary Patterson ◽  
Markéta Braun Kohlová

2020 ◽  
Vol 29 (3) ◽  
pp. 365-374
Author(s):  
Danielle Schönborn ◽  
Faheema Mahomed Asmail ◽  
Karina C. De Sousa ◽  
Ariane Laplante-Lévesque ◽  
David R. Moore ◽  
...  

Purpose This study investigated user characteristics, help-seeking behavior, and follow-up actions of people who failed an app-based digits-in-noise hearing screening test, considering their stage of change. Method Test and user characteristics of 3,092 listeners who failed the test were retrospectively analyzed. A posttest survey determining follow-up (verb) actions was sent to listeners who failed the test ( n = 1,007), of which 59 responded. Results The majority of listeners were in the precontemplation stage (75.5%). Age and stage of change were significant ( p < .05) predictors of the digits-in-noise speech recognition threshold (DIN SRT). Listeners in the precontemplation stage were significantly younger than in other stages ( p < .05). Posttest survey response rate was low (5.9%). Of those, most (82.4%) did not think they had a hearing loss. Only 13.6% followed up with an audiologist. Conclusion Older people presented with poorer DIN SRTs and were typically in a more advanced stage of change. The majority of those who did not follow up after failing the screening test did not believe they had a hearing loss. A combination of factors, including poor DIN SRT, older age, and a more advanced stage of change inclined participants to follow up with audiological care.


2003 ◽  
Vol 3 (4) ◽  
pp. 365-385 ◽  
Author(s):  
Patricia J Jordan ◽  
Colleen A Redding ◽  
Nicholas A Troop ◽  
Janet Treasure ◽  
Lucy Serpell

2019 ◽  
Vol 28 (3S) ◽  
pp. 802-805 ◽  
Author(s):  
Marieke Pronk ◽  
Janine F. J. Meijerink ◽  
Sophia E. Kramer ◽  
Martijn W. Heymans ◽  
Jana Besser

Purpose The current study aimed to identify factors that distinguish between older (50+ years) hearing aid (HA) candidates who do and do not purchase HAs after having gone through an HA evaluation period (HAEP). Method Secondary data analysis of the SUpport PRogram trial was performed ( n = 267 older, 1st-time HA candidates). All SUpport PRogram participants started an HAEP shortly after study enrollment. Decision to purchase an HA by the end of the HAEP was the outcome of interest of the current study. Participants' baseline covariates (22 in total) were included as candidate predictors. Multivariable logistic regression modeling (backward selection and reclassification tables) was used. Results Of all candidate predictors, only pure-tone average (average of 1, 2, and 4 kHz) hearing loss emerged as a significant predictor (odds ratio = 1.03, 95% confidence interval [1.03, 1.17]). Model performance was weak (Nagelkerke R 2 = .04, area under the curve = 0.61). Conclusions These data suggest that, once HA candidates have decided to enter an HAEP, factors measured early in the help-seeking journey do not predict well who will and will not purchase an HA. Instead, factors that act during the HAEP may hold this predictive value. This should be examined.


Crisis ◽  
2015 ◽  
Vol 36 (4) ◽  
pp. 267-273 ◽  
Author(s):  
Hajime Sueki ◽  
Jiro Ito

Abstract. Background: Nurturing gatekeepers is an effective suicide prevention strategy. Internet-based methods to screen those at high risk of suicide have been developed in recent years but have not been used for online gatekeeping. Aims: A preliminary study was conducted to examine the feasibility and effects of online gatekeeping. Method: Advertisements to promote e-mail psychological consultation service use among Internet users were placed on web pages identified by searches using suicide-related keywords. We replied to all emails received between July and December 2013 and analyzed their contents. Results: A total of 139 consultation service users were analyzed. The mean age was 23.8 years (SD = 9.7), and female users accounted for 80% of the sample. Suicidal ideation was present in 74.1%, and 12.2% had a history of suicide attempts. After consultation, positive changes in mood were observed in 10.8%, 16.5% showed intentions to seek help from new supporters, and 10.1% of all 139 users actually took help-seeking actions. Conclusion: Online gatekeeping to prevent suicide by placing advertisements on web search pages to promote consultation service use among Internet users with suicidal ideation may be feasible.


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