Esben Kjems Jensen
Biographic Data
| ID | 7522013 |
|---|---|
| NAME | Esben Kjems Jensen |
| GIVEN NAMES | Esben Kjems |
| FAMILY NAME | Jensen |
| SIGNATURE | JENSEN E K |
| AFFILIATIONS | Mental Health Services |
| ORCID | 0000-0002-9689-3776 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Choosing the right treatment - combining clinicians’ expert knowledge with data-driven predictions
In 90.1% of cases, the hybrid model ranked the actual disorder treated as either the highest (67.3%) or second-highest (22.8%) on the test data. This emphasizes that instead of suggesting a single disorder to be treated, the model can offer the probabilities for multiple disorders. This allows individuals seeking treatment or their therapists to incorporate this information as an additional data-driven factor when collectively deciding on which t…
Therapist perceptions of the implementation of a new screening procedure using the ItFits-toolkit in an iCBT routine care clinic
The ItFits-toolkit appears to have been an effective mediator of the implementation process. The therapists were aided in the process of change, resulting in an enhanced ability to target the patients who can benefit from the treatment program, less expenditure of time on the wrong population, and more satisfied therapists
An analysis of patient motivation for seeking online treatment for binge eating disorder—A mixed methods study combining systematic text condensation with sentiment analysis
Because motivation type does not influence online treatment to the same degree as it would in face-to-face treatment it indicates that the typical barriers to treatment may be less crucial in an online setting. This should be considered during intake; as less motivated patients may be able to adhere better to online treatment, because the latter imposes fewer barriers of the kind that only strong motivation can overcome. The fact that motivation …
Early development of treatment motivation predicts adherence and symptom reduction in an internet-based guided self-help program for binge eating disorder
The results indicated that patients entering online treatment for BED feel highly motivated. However, baseline treatment motivation could not significantly predict treatment completion, which contradicts previous research. The significant predictive ability of early measures of treatment motivation supports the clinical relevance of monitoring the development of early changes to tailor and optimize individual patient care. Further research is nee…
No prominent works on this page.
An analysis of patient motivation for seeking online treatment for binge eating disorder—A mixed methods study combining systematic text condensation with sentiment analysis
Because motivation type does not influence online treatment to the same degree as it would in face-to-face treatment it indicates that the typical barriers to treatment may be less crucial in an online setting. This should be considered during intake; as less motivated patients may be able to adhere better to online treatment, because the latter imposes fewer barriers of the kind that only strong motivation can overcome. The fact that motivation …
Early development of treatment motivation predicts adherence and symptom reduction in an internet-based guided self-help program for binge eating disorder
The results indicated that patients entering online treatment for BED feel highly motivated. However, baseline treatment motivation could not significantly predict treatment completion, which contradicts previous research. The significant predictive ability of early measures of treatment motivation supports the clinical relevance of monitoring the development of early changes to tailor and optimize individual patient care. Further research is nee…
Therapist perceptions of the implementation of a new screening procedure using the ItFits-toolkit in an iCBT routine care clinic
The ItFits-toolkit appears to have been an effective mediator of the implementation process. The therapists were aided in the process of change, resulting in an enhanced ability to target the patients who can benefit from the treatment program, less expenditure of time on the wrong population, and more satisfied therapists
Choosing the right treatment - combining clinicians’ expert knowledge with data-driven predictions
In 90.1% of cases, the hybrid model ranked the actual disorder treated as either the highest (67.3%) or second-highest (22.8%) on the test data. This emphasizes that instead of suggesting a single disorder to be treated, the model can offer the probabilities for multiple disorders. This allows individuals seeking treatment or their therapists to incorporate this information as an additional data-driven factor when collectively deciding on which t…
Computer Science (4 works) · Psychology (4 works) · Medicine (3 works) · Binge eating (2 works) · Binge-eating disorder (2 works) · Bulimia nervosa (2 works) · Clinical Psychology (2 works) · Clinical Psychology (2 works) · Eating disorders (2 works) · Eating Disorders and Behaviors (2 works)